Weighted nucleoli and dually essential coalitions
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Abstract
We consider linearly weighted versions of the least core and the (pre)nuceolus and investigate the reduction possibilities in their computation. We slightly extend some wellknown related results and establish their counterparts by using the dual game. Our main results imply, for example, that if the core of the game is not empty, all dually inessential coalitions (which can be weakly minorized by a partition in the dual game) can be ignored when we compute the percapita least core and the percapita (pre)nucleolus from the dual game. This could lead to the design of polynomial time algorithms for the percapita (and other monotone nondecreasingly weighted versions of the) least core and the (pre)nucleolus in specific classes of balanced games with polynomial many dually essential coalitions.
Keywords
Percapita (pre)nucleolus Least core Computation1 Introduction
The nucleolus (Schmeidler 1969) is one of the major singlevalued solution concepts for transferable utility cooperative games. It seemingly depends on all coalitional values, but a closer look reveals the inherent high redundancy in its definition. Indeed, as Brune (1983), and later Reijnierse and Potters (1998) have proved: in any nplayer game there are at most \(2n2\) coalitions which actually determine the nucleolus. Unfortunately, the identification of these nucleolusdefining coalitions is no less laborious as computing the nucleolus itself. On the other hand, if special properties of the game enable us to specify a priori a polynomial size characterization family of coalitions for the nucleolus, then we can compute it in polynomial time (in the number of players).
There are several classes of balanced games for which polynomial time nucleolus algorithms are available in the literature. The key to the efficiency of some of these algorithms (e.g. in case of assignment games) is Huberman’s (1980) theorem stating that in a balanced game all nucleolusdefining coalitions are essential (cannot be weakly majorized by a partition) in the game, hence the inessential ones can be ignored. Although typically not explicitly mentioned, but several other known polytime algorithms (e.g. in case of fixedtree games) rely on the dual counterpart of Huberman’s result: in computing the nucleolus of a balanced game, all dually inessential coalitions (which can be weakly minorized by a partition in the dual game) can be ignored.
Our aim is to investigate what kinds of weighted versions of the nucleolus can also be computed by taking into account only coalitions in these families. Since the above mentioned reducibility results require nonemptiness of the core, our domain will also be the class of balanced games. We are mostly concerned about the percapita nucleolus (Grotte 1970, 1972), so we restrict our study to linear weight systems. On the other hand, we allow weights that depend not only on the size, but also on the value of the coalitions. In particular, we allow the weight of a coalition to be equal to its value (provided it is positive), thus some of our results also apply to the proportional nucleolus of a balanced game (with only positive coalitional values).
The nucleolus is based on the coalitional surplusses (the difference between the payoff to and the value of the coalition). This measure, however, does not take into account neither the size, nor the value (or any other characteristic that maybe important for an application) of the coalitions. Various weighted nucleoli (based on weighted surplus measures) were considered by several authors, but mostly from an axiomatization point of view, see e.g. (Derks and Peters 1998; Derks and Haller 1999; Kleppe 2010; Kleppe et al. 2016; Calleja et al. 2018). We address issues in connection with their computation.
In general, a linearly weighted nucleolus can be determined by the very same methods as the (standard) nucleolus, only straightforward adjustments are needed that only negligibly effect the performance. This is particularly true for the most frequently applied sequential linear programming approach pioneered by Kopelowitz (1967) (for a recent implementation finely tuned even for large games, see (Nguyen and Thomas 2016)). On the other hand, and in contrast to the rich literature on the computation of the (standard) nucleolus in specific classes of games, we can only mention the algorithm by Huijink et al. (2015) that computes the percapita nucleolus in bankruptcy games. One of our results might shed light on a possible reason for this phenomenon. We demonstrate (in Example 3) that the family of essential coalitions is not sufficient to determine the percapita nucleolus, not even in a balanced game, so Huberman’s (1980) reducibility result cannot be used in the computation of the percapita nucleolus.
We find, however, that if we compute the nucleolus of a balanced game from the dual coalitional values, Huberman’s idea works, not just for the (standard) nucleolus (that is implicitly the basis for many known efficient algorithms), but also for the percapita and other monotone nondecreasingly weighted nucleoli. We prove (in Theorem 4) that if the core of the game is not empty, all dually inessential coalitions (those which can be weakly minorized by a partition in the dual game) can be ignored when we compute the percapita (or other monotone nondecreasingly weighted versions of the) nucleolus from the dual game. We believe that this observation could become the theoretical basis for various polynomial time algorithms (yet to be) designed for the percapita nucleolus in specific classes of balanced games known to have polynomial many dually essential coalitions (e.g. assignment games, fixedtree games). Other candidates for this endeavour might be the wellknown classes of games whose duality relations are discussed by Oishi and Nakayama (2009). The usefulness of looking at the dual games also in the axiomatizations of solutions is underlined by Oishi et al. (2016).
The organization of the paper is as follows. We collect the necessary general preliminaries and introduce the linear weight systems in the next section. In Sect. 3, we discuss weighted least cores, since computing them is the first step in finding the weighted (pre)nucleoli. We present properties of the weight function under which the family of essential coalitions is sufficient to determine the weighted least core, and also when the family of dually essential coalitions is sufficient to determine the weighted least core in the dual game of a balanced game. In Sect. 4, we present the weighted primal and dual versions of the lexicographic center procedure (Maschler et al. 1979) that sequentially reduces the set of allowable payoffs until it shrinks to the (pre)nucleolus allocation, and discuss which properties of the weight system make the inessential coalitions, or in the dual version the dually inessential coalitions redundant in these sequential optimization processes when applied to balanced games. In Sect. 5 we discuss how and when we can refine our results by combining the primal and dual restricted descriptions of the standard/percapita least core/(pre)nucleolus. In that last section we also illustrate the simplification potential of applying dual (in)essentiality on the 5player (balanced) cost game discussed by Suzuki and Nakayama (1976).
2 Preliminaries
Given a game v, a payoff vector\(x\in \mathbb {R}^N\) is called efficient, if \(x(N)=v(N)\); coalitionally rational, if \(x(S) \ge v(S)\) for all \(S \subseteq N\); where, by the standard notation, \(x(S)=\sum _{i\in S} x_i\) if \(S\ne \emptyset \), and \(x(\emptyset )=0\). We denote by \(\mathbf {Ef}(v)\) the set of efficient payoff vectors called the preimputation set, and by \(\mathbf {Co}(v)\) the set of efficient and coalitionally rational payoff vectors called the core of the game v. Games with a nonempty core are called balanced.
The excess\(e(S,x,v)=v(S)x(S)\) is the usual measure of gain (or loss if negative) to coalition \(S\subseteq N\) in game v if its members depart from allocation \(x\in \mathbb {R}^N\) in order to form their own coalition. Note that in any game v, \(e(\emptyset ,x,v)=0\) for all \(x\in \mathbb {R}^N\), and the core is the set of efficient allocations which yield nonpositive excess for all nontrivial coalitions. It will be more convenient to use the negative excess \(f(S,x,v):=e(S,x,v)\), we call it the surplus of coalition S at allocation x in game v.
The dual game\((N, v^*)\) of game (N, v) is defined by \(v^* (S)=v(N)v(N{\setminus } S)\) for all \(S\subseteq N\). Notice that \(v^*(\emptyset )=0\), so \(v^*\) is indeed a game, and \(v^*(N)=v(N)\), so \(\mathbf {Ef}(v^*)=\mathbf {Ef}(v)\) for any game v. The name dual is explained by the relation \({v^{*}}^{*}(S)=v(S)\) for all \(S\subseteq N\).
We will investigate which families of nontrivial coalitions are sufficient to determine a solution in a game and which coalitions are redundant. Two types of coalitions will be considered.
The standard surplus (excess) does not take into account neither the size, nor the value (or any other characteristic that maybe important for an application) of the coalitions. More general excess functions were considered by several authors, but we restrict ourselves to the weighted versions that preserve the linearity of the measure with respect to the payoff variables.
We say that a weight function is subadditive, if \(S\cap T=\emptyset \) implies \(q(S)+q(T)\ge q(S\cup T)\) for all \(S,T\in \mathcal{N}\); superadditive, if the inequality is reversed; additive, if both subadditive and superadditive; monotone nondecreasing, if \(S\subset T\) implies \(q(S)\le q(T)\) for all \(S,T\in \mathcal{N}\); and monotone nonincreasing, if the inequality is reversed.

the (standard) least core and nucleolus, if we take the monotone and subadditive (but not superadditive) weight function \(q(S)=1\) for all \(S\in \mathcal{N}\);

the percapita least core and nucleolus, if we take the monotone and additive weight function \(q(S)=S\) for all \(S\in \mathcal{N}\);

for positivevalued game v (i.e. \(v(S)>0\) for all \(S\ne \emptyset \)), the proportional least core and nucleolus, if we take the weight function \(q(S)=v(S)\) for all \(S\in \mathcal{N}\).
3 Weighted least cores
We will also consider certain restricted versions when only coalitions coming from a nonempty family \(\mathscr {M}\subseteq \mathscr {N}\) are taken into account. The family \(\mathscr {M}\) will always be “rich enough” so that the restricted qleast core \(\mathbf {LC}_q(\mathcal{M},v)\) will always be a nonempty polytope like the unrestricted one \(\mathbf {LC}_q(v)=\mathbf {LC}_q(\mathcal{N},v)\). For the same reason, also in the restricted case \(\alpha ^1_q(\mathcal{M},v)\) will always be well defined.
The following characterizations of weighted leastcore allocations in terms of balanced collections can be easily obtained by standard LP duality arguments applied to the LP descriptions (7) or (8).
Proposition 1
 1.
At x, the coalition minimizes \(f_q(S,x,v)\) over all coalitions \(S\in \mathcal{N}\) in game v;
 2.
At x, the coalition maximizes \(g_q(T,x,v^*)\) over all coalitions \(T\in \mathcal{N}\) in the dual game \(v^*\).
For the standard least core, the first type of characterization (in terms of v) is wellknown (cf. e.g. Peleg and Sudhölter 2003, p.183).
There is a close relationship between the two types of (minimal) balanced collection(s) mentioned in Proposition 1. If, at a qweighted least core allocation x, we replace all coalitions of a (minimal) balanced collection contained in the family \(\mathcal{S}^1(x)\) of coalitions with minimum qsurplus \(f_q(S,x,v)\) with their complements, we get a (minimal) balanced collection contained in the family \(\mathcal{T}^1(x)\) of coalitions with maximum transformed dual qsurplus \(g_q(N{\setminus } S,x,v^*)\), and vice versa.
We now identify families of redundant coalitions for weighted least cores.
Theorem 1
 1.
In a balanced game v, all inessential coalitions are redundant for \(\mathbf {LC}_q(v)\) with a subadditive weight function q. In particular, for the standard least core \(\mathbf {LC}(v)=\mathbf {LC}(\mathcal{E}(v),v)\), and for the percapita least core \(\mathbf {LC}_{pc}(v)=\mathbf {LC}_{pc}(\mathcal{E}(v),v)\).
 2.
In a nonbalanced game v, all inessential coalitions are redundant for \(\mathbf {LC}_q(v)\) with a superadditive weight function q. In particular, for the percapita least core \(\mathbf {LC}_{pc}(v)=\mathbf {LC}_{pc}(\mathcal{E}(v),v)\).
 3.
In any game v, all inessential coalitions are redundant for \(\mathbf {LC}_q(v)\) with an additive weight function q. In particular, for the percapita least core \(\mathbf {LC}_{pc}(v)=\mathbf {LC}_{pc}(\mathcal{E}(v),v)\).
Proof
 1.
\(\alpha \ge 0\) (i.e. v is balanced) and q is a subadditive weight function.
 2.
\(\alpha < 0\) (i.e. v is not balanced) and q is a superadditive weight function.
 3.
q is an additive weight function.
As the following example demonstrates, the second and third statements in Theorem 1 are not true for the standard least core \(\mathbf {LC}\).
Example 1
Consider the following game on player set \(N=\{1,2,3,4\}\) given by \(v(N)=v(14)=v(24)=v(124)=v(134)=v(234)=18\), \(v(34)=12\), \(v(12)=v(123)=6\), and \(v(R)=0\) for all other coalitions \(R\in \mathcal{N}\).
It is easily checked that v is superadditive, but not balanced, e.g. \(\frac{1}{2}v(12)+\frac{1}{2}v(134)+\frac{1}{2}v(234)=21>18=v(N)\). The maximum uniformly guaranteed surplus is \(\alpha ^1(v)=2\), the standard least core is a singleton \(\mathbf {LC}(v) = \{x=(2,2,0,14)\}\). Indeed, at allocation x, the family of coalitions with smallest surplus (\(=2\)) is \(\mathcal{S}^1(x)=\{12, 14, 24\), \(123, 134, 234\}\) that is the union of the (minimal) balanced collections \(\{12, 134, 234\}\), \(\{14, 123, 234\}\), and \(\{24, 123, 134\}\), so by Proposition 1, \(x\in \mathbf {LC}(v)\). The uniqueness of this least core allocation comes from the “full rank nature” of \(\mathcal{S}^1(x)\).
On the other hand, if we take into account only the essential coalitions \(\mathcal{E}(v)=\{1,2,3,4,12,14,24,34\}\) in (6), we get another uniform surplus level \(\alpha ^1(\mathcal{E}(v),v)=\frac{6}{5}\), and another (singleton) least core \(\mathbf {LC}(\mathcal{E}(v),v) = \{y=(\frac{12}{5},\frac{12}{5},\frac{6}{5},\frac{72}{5})\}\). Indeed, at allocation y, the family of essential coalitions with smallest surplus (\(=\frac{6}{5}\)) is \(\mathcal{S}^1(\mathcal{E}(v),y)=\{3, 12, 14, 24\}\) that is itself a (minimal) balanced collection of “full rank”, so by Proposition 1, \(y\in \mathbf {LC}(\mathcal{E}(v),v)\), and y is the unique \(\mathcal{E}(v)\)restricted least core allocation.
In contrast, and as an illustration of the second statement in Theorem 1, the uniformly guaranteed percapita surplus is \(\alpha ^1_{pc}(v)=\frac{3}{4}\), the (singleton) percapita least core is \(\mathbf {LC}_{pc}(v) = \{z=(\frac{9}{4},\frac{9}{4},\frac{3}{4},\frac{57}{4})\}\). Indeed, at allocation z, the family of coalitions with smallest percapita surplus (\(=\frac{3}{4}\)) is \(\mathcal{S}_{pc}^1(z)=\{3, 12, 14, 24, 123, 134, 234\}\) that is the union of the balanced collections \(\{3, 12, 14, 24\}\) and the above \(\mathcal{S}^1(x)\), so by Proposition 1, \(z\in \mathbf {LC}_{pc}(v)\). Since \(\{3, 12, 14, 24\}\subset \mathcal{E}(v)\) and it is itself a “full rank” (minimal) balanced collection, the restriction to the family of essential coalitions gives the same \(\alpha ^1_{pc}(\mathcal{E}(v),v)=\frac{3}{4}\) and (singleton) least core \(\mathbf {LC}_{pc}(\mathcal{E}(v),v) = \{(\frac{9}{4},\frac{9}{4},\frac{3}{4},\frac{57}{4})\}\) as in the unrestricted case. \(\square \)
Let us see redundant coalitions in the dual descriptions of weighted least cores.
Theorem 2
In a balanced game v, all dually inessential coalitions are redundant for \(\mathbf {LC}_q(v)=\mathbf {LC}^*_q(v^*)\) with a monotone nondecreasing weight function q. In particular, for the standard least core \(\mathbf {LC}(v)=\mathbf {LC}^*(\mathcal{E}^*(v^*),v^*)\), and for the percapita least core \(\mathbf {LC}_{pc}(v)=\mathbf {LC}^*_{pc}(\mathcal{E}^*(v^*),v^*)\).
Proof
Since \(T_1,T_2\in \mathcal{E}^*(v^*)\), the above argument can be independently done for any dually inessential \(T\in \mathcal{N}{\setminus }\mathcal{E}^*(v^*)\). The claims for the special least cores follow from the fact that their respective weight functions are monotone nondecreasing. \(\square \)
As the following example demonstrates, balancedness of the game in Theorem 2 is needed for both the standard least core \(\mathbf {LC}\) and the percapita least core \(\mathbf {LC}_{pc}\).
Example 2
Consider the dual game \(v^*\) of the 4player nonbalanced game v in Example 1: \(v^*(N)=v^*(14)=v^*(24)=v^*(123)=v^*(124)=v^*(134)=v^*(234)=18\), \(v^*(4)=v^*(34)=12\), \(v^*(12)=6\), and \(v^*(R)=0\) for all other coalitions \(R\in \mathcal{N}\).
In the dual description (10) for the standard least core, the minimum uniformly guaranteed transformed dual surplus is \(\beta ^1(v^*)=2\), and the set of optimal solutions is the singleton \(\mathbf {LC}^*(v^*) = \{x=(2,2,0,14)\}\), that is, of course, the same as \(\mathbf {LC}(v)\) in Example 1. We can also check it directly by the second characterization in Proposition 1. At allocation x, the family of coalitions with largest transformed dual surplus (\(=2\)) is \(\mathcal{T}^1(x)=\{1, 2, 4, 13, 23, 34\}\) that is the union of the partitions \(\{1, 2, 34\}\), \(\{1, 4, 23\}\), and \(\{2, 4, 13\}\), so \(x\in \mathbf {LC}^*(v^*)\) indeed. The uniqueness comes from the “full rank nature” of \(\mathcal{T}^1(x)\). Notice that \(\mathcal{T}^1(x)\) consists of the complements of the coalitions in \(\mathcal{S}^1(x)\) in Example 1 and \(\beta ^1(v^*)=\alpha ^1(v)\).
On the other hand, if we take into account only the dually essential coalitions \(\mathcal{E}^*(v^*)=\{1,2,3,4\}\) in (10), we get another minimum uniformly guaranteed transformed dual surplus level \(\beta ^1(\mathcal{E}^*(v^*),v^*)=\frac{3}{2}\), and another (singleton) optimal solution set \(\mathbf {LC}^*(\mathcal{E}^*(v^*),v^*) = \{s=(\frac{3}{2},\frac{3}{2},\frac{3}{2},\frac{27}{2})\}\). At this allocation, \(\mathcal{T}^1(\mathcal{E}^*(v^*),s)=\{1, 2, 3, 4\}\) that is itself a partition of “full rank”, so from Proposition 1 we get that \(s\in \mathbf {LC}^*(\mathcal{E}^*(v^*),v^*)\), and s is the unique such allocation.
In the dual description (10) for the percapita least core, the minimum uniformly guaranteed transformed dual surplus is \(\beta _{pc}^1(v^*)=\frac{3}{4}\), and the set of optimal solutions is the singleton \(\mathbf {LC}_{pc}^*(v^*) = \{z=(\frac{9}{4},\frac{9}{4},\frac{3}{4},\frac{57}{4})\}\), that is, of course, the same as \(\mathbf {LC}_{pc}(v)\) in Example 1. We can also confirm this by the second characterization in Proposition 1. Indeed, at allocation z, the family of coalitions with largest transformed dual percapita surplus (\(=\frac{3}{4}\)) is \(\mathcal{T}_{pc}^1(z)=\{1, 2, 4, 13, 23, 34, 124\}\) that is the union of the partitions \(\{1, 2, 34\}\), \(\{1, 4, 23\}\), \(\{2, 4, 13\}\), and the (minimal) balanced collection \(\{13, 23, 34, 124\}\), so \(t\in \mathbf {LC}_{pc}^*(v^*)\) indeed. The uniqueness comes again from the “full rank nature” of \(\mathcal{T}_{pc}^1(z)\). Notice also here that \(\mathcal{T}_{pc}^1(z)\) consists of the complements of the coalitions in \(\mathcal{S}_{pc}^1(z)\) in Example 1 and \(\beta _{pc}^1(v^*)=\alpha _{pc}^1(v)\).
On the other hand, since only the singleplayer coalitions are dually essential and \(g_{pc}(k,.,v^*)=\frac{f(k,.,v^*)}{3}=\frac{1}{3}g(k,.,v^*)\) for each \(k\in N\), the \(\mathcal{E}^*(v^*)\)restricted optimization in the percapita case gives the same set of optimal solutions as in the standard case. Thus, \(\mathbf {LC}_{pc}^*(\mathcal{E}^*(v^*),v^*) = \{s=(\frac{3}{2},\frac{3}{2},\frac{3}{2},\frac{27}{2})\}\). Only the optimum value is scaled \(\beta _{pc}^1(\mathcal{E}^*(v^*),v^*)=\frac{1}{2}=\frac{1}{3}\beta ^1(\mathcal{E}^*(v^*),v^*)\). At this allocation, \(\mathcal{T}_{pc}^1(\mathcal{E}^*(v^*),s)=\{1, 2, 3, 4\}\) that is itself a partition of “full rank”, so from Proposition 1 we get that \(s\in \mathbf {LC}_{pc}^*(\mathcal{E}^*(v^*),v^*)\), and s is the unique such allocation. \(\square \)
4 Weighted nucleoli
The (pre)nucleolus (Schmeidler 1969) is a nonempty set of (pre)imputations that consists of a single element, called the (pre)nucleolus allocation. The following alternative definition (Maschler et al. 1979) will serve us better here.

\(\rho \) is well defined and finite;

\(\alpha _q^1(v)=\alpha _q^1<\alpha _q^2<\cdots < \alpha _q^{\rho }\) are well defined;

\(\mathbf {LC}_q(v)=X^1 \supseteq X^2 \supseteq \cdots \supseteq X^{\rho }\) are nonempty polytopes;

\(\varDelta _1 \cup \varDelta _2 \cup \cdots \cup \varDelta _{\rho }\) forms a partition of \(\mathcal{N}\),

if \(S\in \varDelta _k\) then \(v(S)+q(S)\alpha _q^k = \eta _q(S)\),
We will also consider certain restricted versions, but only to a nonempty family of coalitions \(\mathscr {M}\subseteq \mathscr {N}\) that is “rich enough” so that all above statements will hold true also in the restricted cases.
We now identify families of redundant coalitions for weighted prenucleoli. The following theorem is a slight generalization of Huberman’s (1980) theorem on the standard (pre)nucleolus that is fundamental for the efficient computability of the (pre)nucleolus in various types of balanced games with polynomially many essential coalitions, as it is the case e.g. in assignment games (Solymosi and Raghavan 1994).

in a balanced game, all inessential coalitions are redundant for the nucleolus.
Theorem 3
In a balanced game v, all inessential coalitions are redundant for \(\mathbf {Nu}_q(v)\) with a monotone nonincreasing weight function q. In particular, for the standard prenucleolus \(\mathbf {Nu}(v)=\mathbf {Nu}(\mathcal{E}(v),v)\).
Proof
Let \(S\in \mathcal{N}{\setminus }\mathcal{E}(v)\) be inessential in game v, because of the partition \(S=S_1\cup S_2\) with \(S_1,S_2\in \mathcal{E}(v)\) and \(v(S)\le v(S_1)+v(S_2)\). For simplicity of notation, we assume (without loss of generality) that the weakly majorizing partition consists only of \(k=2\) subcoalitions.
We prove that in all iterations \(r=1,\ldots ,\rho \) of algorithm (13) the (inequality or equality) constraint related to S is redundant, because it is implied by the constraints related to \(S_1\) and \(S_2\).
Since iteration \(r=1\) determines \(\alpha _q^1(v)\) and the qweighted least core, the redundancy of inequalities related to inessential coalitions in a balanced game was shown in claim 1 of Theorem 1 using (11) even under the weaker assumption of subadditivity on the weight function. Observe that the same argument proves our claim in any other iteration \(r>1\) in which all subcoalitions in the weakly majorizing essential partition are still unsettled (i.e. \(S_i\in \varSigma ^{r1}\) for all \(i=1,\ldots ,k\)), hence all related constraints are inequalities like in (11).
Finally, suppose that at the end of some iteration \(r\ge 1\) coalition S becomes settled (i.e. \(S\in \varDelta _{r}\)). This is equivalent to saying that all subcoalitions in the weakly majorizing essential partition have become settled by the end of that iteration. For simplicity, let \(S_2\in \varDelta _{r}\) be the last one to become settled. Then all related constraints become equalities in (14), the redundancy of the last constraint, however, follows in the same way, for all subsequent iterations.
In all three cases the constraints related to \(S_1\) and \(S_2\) imply the constraint related to S, hence algorithm (13) yields the same outcomes even if we discard S from all considerations. Since \(S_1,S_2\in \mathcal{E}(v)\), the above arguments can be independently repeated for any inessential \(S\in \mathcal{N}{\setminus }\mathcal{E}(v)\), and the theorem follows.
The constant \(q(S)=1\) for all \(S\in \mathcal{N}\) weight function is monotone nonincreasing, so we get Huberman’s (1980) theorem on the redundancy of inessential coalitions for the standard (pre)nucleolus in balanced games as a corollary. \(\square \)
For completeness, we present (without proof) a characterization of weighted prenucleoli in terms of balanced collections. It is a slight generalization of the characterization given by Wallmeier (1984) for qprenucleoli with monotone nondecreasing and symmetric (i.e. \(q(S)=q(S)\) for all \(S\in \mathcal{N}\)) weight function, that, in turn is a straightforward generalization of Kohhlberg’s (1971) criterion for the standard prenucleolus. Streamlined versions of Kohlberg’s (1971) characterization are given in (Groote Schaarsberg et al. 2013) and (Nguyen 2016) for the standard (pre)nucleolus, and in (Huijink et al. 2015) for the percapita (pre)nucleolus. Similar characterizations in more general and abstract settings that accommodate the weighted versions discussed here can be found in (Maschler et al. 1992) and (Potters and Tijs 1992).
Proposition 2
An efficient payoff allocation x belongs to the qweighted prenucleolus of game v if and only if the family of nontrivial coalitions whose qsurplus at x is at most t is a balanced (or an empty) collection for any \(t\in \mathbb {R}\).
The following example demonstrates that Huberman’s (1980) redundancy result cannot be applied for the percapita (pre)nucleolus, we can not only use essential coalitions, not even in a balanced game (in which case the percapita prenucleolus coincides with the percapita nucleolus). This could partly explain why there are much fewer specialpurpose algorithms proposed in the literature for the percapita (pre)nucleolus than for the standard (pre)nucleolus. A recent exception is the algorithm by Huijink et al. (2015) for the percapita nucleolus of bankruptcy games.
Example 3
Consider the 4player balanced superadditive game: \(v(N)=12\), \(v(12)=v(34)=v(123)=v(124)=v(134)=v(234)=6\), \(v(14)=4\), and \(v(R)=0\) for all other coalitions \(R\in \mathcal{N}\). Let the weight function be \(q(S)=S\) for all \(S\in \mathcal{N}\).
The first iteration of algorithm (13) gives \(\alpha _q^1=0\), so \(X^1=\mathbf {LC}_q(v)=\mathbf {Co}(v)\), and \(\varDelta _1=\{12,34\}\). The second iteration gives \(\alpha _q^2=1\) and \(\varDelta _2=\{14,123,124,134,234\}\). The third iteration gives \(\alpha _q^3=3\) and \(\varDelta _3=\{1,2,3,4,13,23,24\}\), and the algorithm stops. Thus, \(\rho =3\). The only allocation in \(X^3\) (in fact, already in \(X^2\)) is (3, 3, 3, 3), it is the percapita prenucleolus. It is easily checked also by Proposition 2. Indeed, \(\mathcal{S}^1=\varDelta _1\), \(\mathcal{S}^2=\varDelta _1\cup \varDelta _2\), \(\mathcal{S}^3=\varDelta _1\cup \varDelta _2\cup \varDelta _3\) are all balanced families.
Let us now consider only the essential coalitions \(\mathcal{E}(v)=\{1,2,3,4,12,14,34\}\) and initiate algorithm (13) with \(\varSigma ^0:=\mathcal{E}(v)\) instead of \(\mathcal{N}\). Then the first iteration gives again \(\alpha _q^1=0\), so \(X^1=\mathbf {LC}_q(\mathcal{E}(v),v)=\mathbf {Co}(\mathcal{E}(v),v)=\mathbf {Co}(v)\), and \(\varDelta _1=\{12,34\}\). On the other hand, the second iteration gives \(\alpha _q^2=2\) and \(\varDelta _2=\{2,3,14\}\). The third iteration gives \(\alpha _q^3=4\) and \(\varDelta _3=\{1,4\}\), and the algorithm stops. Thus, \(\rho =3\). The only allocation in \(X^3\) (in fact, already in \(X^2\)) is (4, 2, 2, 4), it is the percapita prenucleolus of the \(\mathcal{E}(v)\)restricted game. It is easily checked also by the restricted version of Proposition 2. Indeed, \(\mathcal{S}^1=\varDelta _1\), \(\mathcal{S}^2=\varDelta _1\cup \varDelta _2\), \(\mathcal{S}^3=\varDelta _1\cup \varDelta _2\cup \varDelta _3\) are all balanced families, consisting only of essential coalitions. \(\square \)

\(\widehat{\rho }\) is well defined and finite;

\(\beta _q^1(v^*)=\beta _q^1>\beta _q^2>\cdots >\beta _q^{\widehat{\rho }}\) are well defined;

\(\mathbf {LC}^*_q(v^*)=Y^1 \supseteq Y^2 \supseteq \cdots \supseteq Y^{\rho }\) are nonempty polytopes;

\(\widehat{\varDelta }_1 \cup \widehat{\varDelta }_2 \cup \cdots \cup \widehat{\varDelta }_{\rho }\) forms a partition of \(\mathcal{N}\);

if \(T\in \widehat{\varDelta }_k\) then \(\widehat{\eta }_q(T)q(N{\setminus } T)\beta _q^k = v^*(T)\),

\(\widehat{\rho }=\rho \);

for all \(r=1,\ldots ,\widehat{\rho }=\rho \) we have \(\beta _q^r=\alpha _q^{r}\);

for all \(r=1,\ldots ,\widehat{\rho }=\rho \) we have \(Y^r=X^r\); in particular, \(\mathbf {LC}^*_q(v^*)=Y^1=X^1=\mathbf {LC}_q(v)\) and \(Y^{\widehat{\rho }}=X^{\rho }\) consists of the unique qprenucleolusallocation \(\widehat{\eta }_q=\eta _q\);

for each \(r=1,\ldots ,\widehat{\rho }=\rho \), the family \(\widehat{\varDelta }_r\) consists of the complements of the coalitions in \(\varDelta _r\).
Theorem 4
In a balanced game v, all dually inessential coalitions are redundant for \(\mathbf {Nu}_q(v)\) with a monotone nondecreasing weight function q. In particular, for the standard prenucleolus \(\mathbf {Nu}(v)=\mathbf {Nu}^*(\mathcal{E}^*(v^*),v^*)\) and for the percapita prenucleolus \(\mathbf {Nu}_{pc}(v)=\mathbf {Nu}^*_{pc}(\mathcal{E}^*(v^*),v^*)\).
Proof
Let \(T\in \mathcal{N}{\setminus }\mathcal{E}^*(v^*)\) be dually inessential in game v, because of the partition \(T=T_1\cup T_2\) with \(T_1,T_2\in \mathcal{E}^*(v^*)\) and \(v^*(T_1)+v^*(T_2)\le v^*(T)\). For simplicity of notation, we assume (without loss of generality) that the weakly minorizing partition consists only of \(k=2\) subcoalitions.
We prove that in all iterations \(r=1,\ldots ,\rho \) of algorithm (15) the (inequality or equality) constraint related to T is redundant, because it is implied by the constraints related to \(T_1\) and \(T_2\).
Since iteration \(r=1\) determines \(\beta _q^1(v^*)\) and the qweighted least core, the redundancy of inequalities related to dually inessential coalitions in a balanced game was shown in Theorem 2. Observe that the same argument proves our claim in any other iteration \(r>1\) in which all subcoalitions in the weakly minorizing dually essential partition are still unsettled (i.e. \(T_i\in \widehat{\varSigma }^{r1}\) for all \(i=1,\ldots ,k\)), hence all related constraints are inequalities like in (12).
Finally, suppose that at the end of some iteration \(r\ge 1\) coalition T becomes settled (i.e. \(T\in \widehat{\varDelta }_{r}\)). This is equivalent to saying that all subcoalitions in the weakly minorizing dually essential partition have become settled by the end of that iteration. For simplicity, let \(T_2\in \widehat{\varDelta }_{r}\) be the last one to become settled. Then all related constraints become equalities in (16), the redundancy of the last constraint, however, follows in the same way, for all subsequent iterations.
In all three cases the constraints related to \(T_1\) and \(T_2\) imply the constraint related to T, hence algorithm (15) yields the same outcomes even if we discard T from all considerations. Since \(T_1,T_2\in \mathcal{E}^*(v^*)\), the above arguments can be independently repeated for any dually inessential \(T\in \mathcal{N}{\setminus }\mathcal{E}^*(v^*)\), and the theorem follows.
The claims for the particular (pre)nucleoli follow immediately from the monotone nondecreasing nature of the respective weight functions. \(\square \)
Note that since the constant \(q(S)=1\) for all \(S\in \mathcal{N}\) weight function is monotone nondecreasing, we get the dual counterpart of Huberman’s (1980) theorem that states the redundancy of dually inessential coalitions for the standard (pre)nucleolus in balanced games. This is the implicit basis of various known efficient nucleolus algorithms, e.g. (Megiddo 1978; Granot et al. 1996; Brânzei et al. 2005; van den Brink et al. 2011).
We emphasize that in Theorem 4, balancedness of the game is a necessary condition. To make the point, let us consider the nonbalanced dual game in Example 2: in that game the (standard/percapita) least core consists of a unique allocation that is precisely the (standard/percapita) prenucleolus.
For completeness, we present a Kohlbergtype characterization of weighted prenucleoli in terms of the dual game. It is the dual counterpart of the characterization in Proposition 2, and the analogue of the second characterization of weighted least core allocations in Proposition 1.
Proposition 3
An efficient payoff allocation x belongs to the qweighted prenucleolus of game v if and only if the family of nontrivial coalitions whose transformed dual qsurplus \(g_q(.,x,v^*)\) at x is at least t is a balanced (or an empty) collection for any \(t\in \mathbb {R}\).
We omit the proof, since the standard LP duality arguments that prove Proposition 2 can be straightforwardly adjusted to the dual description (15).
We use the balanced game in Example 3 to illustrate how Theorem 4 can help in calculating, for example, the percapita (pre)nucleolus. Recall that in that game we could not use only the essential coalitions, discarding all inessential coalitions lead to a different allocation. Now we demonstrate that we, however, can omit all coalitions that are inessential in the dual game.
Example 4
Consider the dual game of the 4player balanced superadditive game in Example 3: \(v^*(N)=v^*(13)=v^*(14)=v^*(24)=v^*(123)=v^*(124)=v^*(134)=v^*(234)=12\), \(v^*(23)=8\), and \(v^*(R)=6\) for all other coalitions \(R\in \mathcal{N}\). Let the weight function be \(q(S)=S\) for all \(S\in \mathcal{N}\).
The first iteration of algorithm (15) gives \(\beta _q^1=0\), so \(Y^1=\mathbf {LC}^*_q(v^*)=\mathbf {Co}(v)\), and \(\widehat{\varDelta }_1=\{12,34\}\). The second iteration gives \(\beta _q^2=1\) and \(\widehat{\varDelta }_2=\{23,1,2,3,4\}\). The third iteration gives \(\beta _q^3=3\) and \(\widehat{\varDelta }_3=\{13,14,24,123,124,134,234\}\), and the algorithm stops. Thus, \(\widehat{\rho }=3\). The only allocation in \(Y^3\) (in fact, already in \(Y^2\)) is (3, 3, 3, 3), it is the percapita prenucleolus (cf. Example 3). It is easily checked also by Proposition 3. Indeed, \(\mathcal{T}^1=\widehat{\varDelta }_1\), \(\mathcal{T}^2=\widehat{\varDelta }_1\cup \widehat{\varDelta }_2\), \(\mathcal{T}^3=\widehat{\varDelta }_1\cup \widehat{\varDelta }_2\cup \widehat{\varDelta }_3\) are all balanced families. Notice that \(\widehat{\varDelta }_1\), \(\widehat{\varDelta }_2\), and \(\widehat{\varDelta }_3\) consists of, respectively, the complements of \(\varDelta _1\), \(\varDelta _2\), and \(\varDelta _3\), computed in Example 3. Furthermore, \(\beta _q^r=\alpha _q^r\) for \(r=1,2,3\).
Let us now take only the dually essential coalitions and initiate algorithm (15) with \(\widehat{\varSigma }^0:=\mathcal{E}^*(v^*)=\{1,2,3,4,12,23,34\}\) instead of \(\mathcal{N}\). Then the first iteration gives again \(\beta _q^1=0\), so \(Y^1=\mathbf {LC}^*_q(\mathcal{E}^*(v^*),v^*)=\mathbf {Co}(\mathcal{E}^*(v^*),v^*)=\mathbf {Co}(v)\), and \(\widehat{\varDelta }_1=\{12,34\}\). The second iteration gives \(\beta _q^2=1\) and \(\widehat{\varDelta }_2=\{1,2,3,4,23\}\), and the algorithm stops. Thus, now \(\widehat{\rho }=2\). The only allocation in \(Y^2\) is (3, 3, 3, 3), it is the percapita prenucleolus of the \(\mathcal{E}^*(v^*)\)restricted game, that is the same as the above output of algorithm (15) run with the unrestricted dual input, that, in turn, coincides with the percapita prenucleolus of the game v (cf. Example 3). It is easily checked also by the restricted version of Proposition 3. Indeed, \(\mathcal{T}^1=\widehat{\varDelta }_1\), \(\mathcal{T}^2=\widehat{\varDelta }_1\cup \widehat{\varDelta }_2\) are both balanced families, consisting only of dually essential coalitions. \(\square \)
5 Final remarks
We considered linearly weighted versions of the least core and the (pre)nuceolus and identified characterization sets for these solutions, i.e. families of coalitions that are sufficient to determine the given solution. We demonstrated that almost all of our results require the game to be balanced. We extended some known related results and established their counterparts by using the dual game.
As corollaries for the bestknown special cases, we found that in a balanced game (N, v), the family of essential coalitions \(\mathcal{E}(v)\) (whose value cannot be weakly majorized by a partition of N in the game v) is a characterization set for the standard least core, for the percapita least core, and for the standard (pre)nucleolus (Theorems 1 and 3), but not for the percapita (pre)nucleolus (Example 3). By analogous arguments, we showed that if the dual game \((N,v^*)\) is antibalanced, the family of dually essential coalitions \(\mathcal{E}^*(v^*)\) (whose value cannot be weakly minorized by a partition of N in the dual game \(v^*\)) is a characterization set for the standard least core, for the percapita least core, for the standard (pre)nucleolus, and also for the percapita (pre)nucleolus (Theorems 2 and 4).
5.1 Refinements
Based on the above summary of our results the following questions arise naturally: when, if at all, does the intersection of the families of essential and dually essential coalitions forms a characterization set for the standard least core, for the percapita least core, and for the standard (pre)nucleolus?
First of all, let us specify what it means to combine the primal and dual reduced descriptions, since the first one is in terms of v but the second one is in terms of the dual game \(v^*\).

if the core of balanced game (N, v) is fulldimensional then all inessential coalitions and the complements of all dually inessential coalitions can be ignored when we compute the standard (pre)nucleolus and the standard least core from the values ofv.
Example 5
Consider the 4player balanced superadditive game: \(v(N)=8\), \(v(1)=v(2)=v(3)=v(4)=v(24)=0\), \(v(13)=2\) and \(v(R)=4\) for all other coalitions \(R\in \mathcal{N}\). The dual game: \(v^*(N)=v^*(234)=v^*(134)=v^*(124)=v^*(123)=v^*(13)=8\), \(v^*(24)=6\) and \(v^*(R)=4\) for all other coalitions \(R\in \mathcal{N}\).
Notice that the core is not fulldimensional. In fact, \(\dim (\mathbf {Co}(v))=1\) since \(v(12)+v(34)=v(N)\) as well as \(v(14)+v(23)=v(N)\), thus \(x(12)=x(34)=x(14)=x(23)=4\) over the entire core.
It is easily checked that \(\mathbf {Co}(v)=\mathbf {LC}(v)=\{(y,4y,y,4y): 1\le y\le 4\}\) and (2, 2, 2, 2) is the standard (pre)nucleolus allocation. We get the same outcomes if we take into account only the essential coalitions \(\mathcal{E}(v)=\{1,2,3,4,12,13,14,23,34\}\) in algorithm (13) with the standard weight function \(q(S)=1\) for all \(S\in \mathcal{N}\). Alternatively, we can run this same standard algorithm (13) only with the complements \(\mathcal{F}(v)=\{234,134,124,123,34,23,14,13,12\}\) of the dually essential coalitions \(\mathcal{E}^*(v^*)=\{1,2,3,4,12,14,23,24,34\}\), listed respectively.
The intersection \(\mathcal{E}(v)\cap \mathcal{F}(v)=\{12,13,14,23,34\}\) of these two characterization sets, however, is not sufficient to determine the correct solutions. Indeed, if we run the standard algorithm (13) with \(\varSigma ^0=\mathcal{E}(v)\cap \mathcal{F}(v)\) we get \(\alpha ^1=0\), but the set of optimal solutions \(X^1=\{(y,4y,y,4y): 1\le y<\infty \}\) is a halfline. Since we dropped all 3player coalitions and coalition 24 as inessentials and also dropped all 1player coalitions as complements of dually inessential coalitions, no constraint is left to guarantee nonnegativity for \(x_2\) and \(x_4\). Thus, the intersection \(\mathcal{E}(v)\cap \mathcal{F}(v)\) is not a characterization set for the standard least core and for the standard (pre)nucleolus.
Let us illustrate why this happens and why this can happen only when the core is not fulldimensional, see (Solymosi and Sziklai 2016) for a general proof. We dropped, for example, coalition 124 because it is weakly majorized by its partition \(v(12)+v(4)\ge v(124)\). But we also dropped coalition 4 because it is weakly majorized by its antipartition \(v(124)+v(34)v(N)\ge v(4)\). Since no other partition weakly majorizes coalition 124 and no other antipartition weakly majorizes coalition 4, we cannot leave them both out at the same time. Each one is redundant in the system because the other one is present. Notice that by combining the two weak majorizations we get \(v(4)+v(12)+v(34)v(N)\ge v(4)\), that implies \(v(12)+v(34)\ge v(N)\). Thus, the grand coalition is also weakly majorized, so N is not the only tight coalition over the entire core. \(\square \)

if the core of balanced game v is fulldimensional then the intersection of the family \(\mathcal{E}(v)\) of essential coalitions and the family \(\mathcal{F}(v)\) of the complements of the dually essential coalitions is a characterization set for the percapita least core, or more generally, for any weighted least core with an subadditive and monotone nondecreasing weight function.
We conclude this section by highlighting from a different perspective what is the crucial difference between the standard and the percapita solutions, why the analogous arguments work for the percapita least core but fail to carry further for the percapita (pre)nucleolus.
5.2 Cost games
Naturally all our results carry over for cost games and their dual games, only the straightforward adjustments required by “the smaller, the better” nature of the outcomes must be made. To avoid duplications in terminology, we consider cost game \(c=v^*\) as the dual game of its dual game \(v=c^*\) that is a usual profit game we worked with so far. Hence we are interested in the antisolutions of cost games.
For illustration, we use the 5player cost game set up by Suzuki and Nakayama (1976) to analyze the cost allocation problem related to a cooperative water development project in Japan. Interested in the (anti)nucleolus allocation, the authors found that only one iteration in the ususal sequential LP optimization procedure was needed (already the least anticore turned out to be a singleton), and concluded that the (anti)nucleolus was fully determined by the family of the (\(n1=4\))player coalitions. This real life example also allows us to demonstrate that working with the dual game explicitly and applying the simplification possibilities in the dual descriptions might have some bite. Specifically, we will see that we can arrive at that same result “almost by inspection”, moreover, from the gained “structural insight” we can readily conclude that in this particular cost game the percapita (anti)nucleolus coincides with the standard (anti)nucleolus.
One needs only a hand calculator (and some patience) to check that c is subadditive. It turns out that c is, in fact, strictly subadditive except at coalition 123, so all coalitions but 123 are antiessential in this cost game. Since there is only negligible redundancy with respect to partitions, we cannot utilize the primary restriction possibilities here. Even deciding whether c is antibalanced or not would require some computer help.
It would be also difficult and tedious to detect in the cost game c itself the other kind of exploitable redundancies and identify coalitions that are weakly minorized by an antipartition. But we can easily calculate the dual cost game \(c^*\) and then check again “with paper and pencil” at which coalitions it is strictly superadditive.
As \(c^*_0\) turned out to be balanced, we can also determine its least core and nucleolus from the restricted system. Since the singleplayer coalitions are easily found to have the minimum surplus at \(\eta ^0\) and they form a “full rank” partition of N, we conclude that the least core of \(c^*_0\) is a singleton and \(\eta ^0\) is the nucleolus allocation. Scale retransformation \(\eta _i=c^*(i)+\eta ^0_i\) for \(i=1,\ldots ,5\) gives that the nucleolus allocation in \(c^*\) (the antinucleolus allocation in c) is \(\eta =(709.2,\, 712.2,\, 4124.8,\, 5495.8,\, 4879.8)\), precisely (10 times of) what Suzuki and Nakayama (1976) computed.
Notes
Acknowledgements
Open access funding provided by Corvinus University of Budapest (BCE).
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