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An integrated approach for allocation and scheduling-location problems on graphs

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Abstract

This article uses an integrated approach to solve real-world problems in three areas, namely single machine scheduling, 1-center location on networks and nonrenewable allocation problems. Jobs are stored at vertices and a single machine will be placed in the network. Each job receives an allocation that comes with a specific cost from an expected limited budget. Processing times of jobs are considered continuous functions of the allocation variables multiplied by costs, while release dates are defined as distances from job locations to the machine. We call this problem the scheduling-location problem with job allocation. The goal is to find a location on networks and an allocation to minimize a scheduling objective, makespan. We first consider the problem at a fixed location and propose a combinatorial algorithm that repeatedly solves continuous knapsack problems and runs in quadratic time. Concerning the original problem, we explore some properties of the objective function and develop a polynomial time algorithm to solve it.

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References

  • Balas E, Zemel E (1980) An algorithm for large zero-one knapsack problems. Oper Res 28:1130–1154

    Article  MathSciNet  Google Scholar 

  • Bernheim BD, Whinston MD (1986) Menu Auctions, Resource Allocation, and Economic Influence. Q J Econ 101(1):1–31

    Article  MathSciNet  Google Scholar 

  • Bhattacharya B, Shi Q, Tamir A (2009) Optimal algorithms for the path/tree-shaped facility location problems in trees. Algorithmica 55:601–618

    Article  MathSciNet  Google Scholar 

  • Blazewicz J, Cellary W, Slowinski R, Weglarz J (1986) Scheduling under resource constraints—deterministic models. Ann Oper Res 7

  • Brown D (2002) Career choice and development. John Wiley & Sons, New Jersey

    Google Scholar 

  • Brucker P (2007) Scheduling algorithms. Springer Verlag, Heidelberg

    Google Scholar 

  • Christofides N, Alvarez-Valdes R, Tamarit JM (1987) Project scheduling with resource constraints: a branch and bound approach. Eur J Oper Res 29:262–273

    Article  MathSciNet  Google Scholar 

  • Dawis RV, Lofquist LH (1984) A psychological theory of work adjustment: an individual differences model and its applications. University of Minnesota Press, Minnesota

    Google Scholar 

  • Drexl A (1991) Scheduling of project networks by job assignment. Manag Sci 37(12):1590–1602

    Article  Google Scholar 

  • Drezner Z, Hamacher HW (2002) Facility location—applications and theory. Springer-Verlag, Berlin-Heidelberg

    Book  Google Scholar 

  • Hennes H (2005) Integrated scheduling and location models. Shaker Verlag, Aachen

    Google Scholar 

  • Hennes H, Hamacher HW (2001) Integrated scheduling and location models: single machine makespan problem. Stud Locat Anal 16:77–90

    MathSciNet  Google Scholar 

  • Hessler CJ (2016) Scheduling-location algorithms with application in evacuation planning. Dr Hut Verlag, Müchen

    Google Scholar 

  • Kalsch MT, Drezner Z (2010) Solving scheduling and location problems in the plane simultaneously. Comput Oper Res 37(2):256–264

    Article  MathSciNet  Google Scholar 

  • Kariv O, Hakimi SL (1979) An algorithmic approach to network location problems. I: the \(p\)-centers. SIAM J Appl Math 37:513–538

    Article  MathSciNet  Google Scholar 

  • Kariv O, Hakimi SL (1979) An algorithmic approach to network location problems. II: the \(p\)-medians. SIAM J Appl Math 37:539–560

    Article  MathSciNet  Google Scholar 

  • Krumke SO, Le HM (2020) Robust absolute single machine makespan scheduling-location problem on trees. Oper Res Lett 48:29–32

    Article  MathSciNet  Google Scholar 

  • Krumke SO, Le HM (2022) 2-approximation algorithm for minmax absolute maximum lateness scheduling-location problem. Oper Res Lett 50(6):732–737

    Article  MathSciNet  Google Scholar 

  • Lai TCL, Chianglin CY, Yu PL (2008) Optimal adjustment of competence set with linear programming. Taiwan J Math 12(8):045–2062

    Article  MathSciNet  Google Scholar 

  • Maheriya A, Patel J (2019) Improve makespan in job allocation using modified Hungarian algorithm in cloud computing. In: proceedings: https://api.semanticscholar.org/CorpusID:212731704

  • Peterson GW, Sampson JP, Reardon RC (1991) Career development and services: a cognitive approach. Thomson Brooks/Cole Publishing Co, California

    Google Scholar 

  • Pham VH, Nguyen KT (2020) Inverse anti-\(k\)-centrum problem on networks with variable edge lengths. Taiwan J Math 24(2):501–522

    Article  MathSciNet  Google Scholar 

  • Shahbazia B, Akbarnezhadb A, Reyc D, Ahmadian Fard Fini A (2018) A mathematical job allocation model to maximize career development opportunities for construction workers. In: Proceeding: International Association for automation and robotics in construction (IAARC) 761–766

  • Stinson JP, Davis EW, Khumawala BM (1978) Multiple resource constrained scheduling using branch and bound. AHE Trans 10:252–259

    Google Scholar 

  • Talbot FB (1982) Resource-constrained project scheduling with time-resource trade-offs: the non-preemptive case. Manag Sci 28:1197–1210

    Article  Google Scholar 

  • Wei WH (2013) Robust estimation: location-scale and regression problems. Taiwan J Math 17(3):1055–1093

    Article  MathSciNet  Google Scholar 

  • Wu P, Wang Y, Cheng J, Li Y (2022) An improved mixed-integer programming approach for bi-objective parallel machine scheduling and location. Comput Ind Eng 174:108813

    Article  Google Scholar 

  • Zhang C, Li Y, Cao J, Yang Z, Coelho LC (2022) Exact and metaheuristic methods for the parallel machine scheduling and location problem with delivery time and due date. Comput Oper Res 147:105936

    Article  Google Scholar 

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Acknowledgements

We sincerely appreciate the valuable comments of anonymous referees, which helped to improve the paper. The first author (K.T. Nguyen) would like to thank the Ministry of Education and Training in Vietnam for funding his work under grant number B2024-TCT-22. The corresponding author (H.M Le) would like to thank Van Lang University, Vietnam for funding his work.

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Correspondence to Huy Minh Le.

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Nguyen, K.T., Le, H.M. An integrated approach for allocation and scheduling-location problems on graphs. Comp. Appl. Math. 43, 147 (2024). https://doi.org/10.1007/s40314-024-02650-5

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