Abstract
To identify the sustainability synergies in a collaborative Moroccan dry food wholesale chain, we investigate the financial and ecological effects of implementing horizontal cooperation between three competitor shippers. For business-to-business networks, the key objective is to ensure last-mile delivery to their clients in metropolitan areas. The implementation of this alliance requires studying different aspects, among them the design of the transportation network, fair profit sharing, and collaborative delivery planning. Limited studies have considered the effects of integrating facility location and vehicle routing by addressing multiple goals in the design of a sustainable collaborative supply chain. We model the problem as a periodic two-echelon echelon-periodic location routing problem to integrate different decision levels. In order to investigate the trade-offs between the two opposing goals, a multi-objective approach is adopted. The Epsilon constraint method is used to generate a compromise between economic and ecological impacts. Cost and carbon emission sharing are assessed through the Shapley value mechanism. Furthermore, to determine the effect of parameter changes on the attained savings, a scenario analysis is performed. Results show the positive effect of collaboration among shippers and the importance of using integrated network design models. Environmental considerations in the pursuit of economic goals affect the gains produced and result in various transportation network structures. The performance of the coalition varies under different scenarios. Managerial implications are presented.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Notes
Abbreviations
- k index of suppliers:
-
K ∈ (1,……..F)
- j index of depots:
-
J ∈ (1,……..W)
- i, l, and h indices of customers:
-
I ∈ (1,……..S)
- t index of period:
-
T ∈ (1,……..P)
- \({\mathrm{q}}_{\left(\mathrm{ikt}\right)}\) :
-
Demand of customer i from supplier(product)k for each shipping date t
- \({\mathrm{Fcap}}_{\left(\mathrm{k}\right)}\) :
-
Capacity of supplier k
- \({\mathrm{Wcap}}_{\left(\mathrm{j}\right)}\) :
-
Capacity of depot j
- \({\mathrm{Tcap}}\) :
-
Capacity of truck
- \({\mathrm{Vcap}}\) :
-
Capacity of vehicle
- \({\mathrm{FCT}}\) :
-
Fixed cost of truck
- \({\mathrm{FCV}}\) :
-
Fixed cost of vehicle
- \({\mathrm{H}}_{\mathrm{j}}\) :
-
Fixed cost of opening and operating the depot j
- \({\mathrm{L}}_{\mathrm{j}}\) :
-
Unit transshipment cost of freight in depot j
- \({\mathrm{C}}_{\left(\mathrm{kj}\right)}\) :
-
Cost of sending a truck from supplier k to depot j
- \({\mathrm{C}\alpha}_{\left(\mathrm{ji}\right)}\) :
-
Cost of visiting customer i just after the depot j
- \({\mathrm{C}\beta}_{\left(\mathrm{ij}\right)}\) :
-
Cost of visiting depot j just after customer i
- \({\mathrm{C}\gamma}_{\left(\mathrm{il}\right)}\) :
-
Cost of visiting customer l just after customer i
- \({\mathrm{d}}_{\left(\mathrm{ji}\right)}\) :
-
Distance between depot j and customer i
- \({\mathrm{d}}_{\left(\mathrm{il}\right)}\) :
-
Distance between customer i and customer l
- \({\mathrm{d}}_{\left(\mathrm{ij}\right)}\) :
-
Distance between customer i and depot j
- \({\mathrm{m}}_{\left(\mathrm{ji}\right)}\) :
-
Travel time from depot j to customer i
- \({\mathrm{m}}_{\left(\mathrm{ilj}\right)}\) :
-
Travel time from customer i and customer l in each route from j
- \({\mathrm{m}}_{\left(\mathrm{ij}\right)}\) :
-
Travel time from customer i and depot j
- \({\mathrm{E}}_{\left(\mathrm{T}\_\mathrm{empty}\right)}\) :
-
CO2 emission of an empty truck in kg/km
- \({\mathrm{E}}_{\left(\mathrm{T}\_\mathrm{full}\right)}\) :
-
CO2 emission of full truckload truck in kg/km
- \({\mathrm{E}}_{\left(\mathrm{V}\_\mathrm{empty}\right)}\) :
-
CO2 emission of an empty vehicle in kg/km
- \({\mathrm{E}}_{\left(\mathrm{V}\_\mathrm{full}\right)}\) :
-
CO2 emission of full truckload vehicle in kg/km
- T:
-
Maximum route time
- \({\mathrm{t}}_{\mathrm{ik}}\) :
-
Service time for one unit of product k at delivery point i
- \({\mathrm{f}}_{\left(\mathrm{kjt}\right)}\) :
-
Quantity of the product k sent from supplier k to satellite j in shipping date t
- \({\mathrm{N}}_{\left(\mathrm{kjt}\right)}\) :
-
Number of truck sent from factory k to depot j in shipping date t
- \({\mathrm{R}}_{\left(\mathrm{jt}\right)}\) :
-
Number of vehicles assigned to the open depots j in shipping date t
- \({\mathrm{y}}_{\mathrm{j}}\) :
-
\(\left\{\begin{array}{cc}1& \mathrm{if\ depot\ j\ is\ open}\\ 0& \mathrm{otherwise}\end{array}\right\}\)
- \({\mathrm{w}}_{\mathrm{ij}}\) :
-
\(\left\{\begin{array}{cc}1& \mathrm{if\ client\ is\ assigned\ to\ depot\ j}\\ 0& \mathrm{otherwise}\end{array}\right\}\)
- \({\mathrm{x}\alpha}_{\mathrm{jit}}\) :
-
\(\left\{\begin{array}{cc}1& \mathrm{if\ i\ is\ the\ first\ customer\ in\ each\ route\ starting\ from\ j\ in\ shipping\ date\ t}\\ 0& \mathrm{otherwise}\end{array}\right\}\)
- \({\mathrm{x}\beta}_{\mathrm{ijt}}\) :
-
\(\left\{\begin{array}{cc}1& \mathrm{if\ i\ is\ the\ last\ customer\ in\ each\ route\ starting\ from\ j\ in\ shipping\ date\ t}\\ 0& \mathrm{otherwise}\end{array}\right\}\)
- \({\mathrm{x}\gamma}_{\mathrm{ihjt}}\) :
-
\(\left\{\begin{array}{cc}1& \mathrm{if\ customer\ h\ is\ visited\ after\ customer\ i\ in\ each\ route\ starting\ from\ j\ in\ shipping\ date\ t}\\ 0& \mathrm{otherwise}\end{array}\right\}\)
- \({\mathrm{U}}_{\mathrm{kjit}}\) :
-
Loaded product k on vehicle going from depot j to first customer i in each route starting from j in shipping date t
- \({\mathbf{U}}_{\mathbf{kihjt}}\)asd:
-
Loaded product k on vehicle going from customer i to costumer h in each route starting from j in shipping date t
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Conceptualization: Hanan Ouhader; methodology: Hanan Ouhader; formal analysis and investigation: Hanan Ouhader; data curation: Hanan Ouhader; visualization: Hanan Ouhader; writing—original draft: Hanan Ouhader; writing—review and editing: Hanan Ouhader and Malika Elkyal; supervision: Hanan Ouhader and Malika Elkyal.
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Ouhader, H., EL kyal, M. Collaborative location routing problem for sustainable supply chain design with profit sharing. Environ Sci Pollut Res 30, 90099–90120 (2023). https://doi.org/10.1007/s11356-023-27788-3
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DOI: https://doi.org/10.1007/s11356-023-27788-3