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Soft Computing
Erschienen in: Soft Computing 4/2020

05.04.2019 | Focus

Bi-level programming problem in the supply chain and its solution algorithm

verfasst von: Haiyan Luo, Linzhong Liu, Xun Yang

Erschienen in: Soft Computing | Ausgabe 4/2020

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Abstract

Enterprise-wide supply chain planning problems naturally exhibit a multi-level decision network structure, where the upper level of a hierarchy may have his objective function and decision space partly determined by other levels. In addition, each planner’s control instruments may allow him to influence the policies at other levels and thereby to improve his own objective function. As a tool, bi-level programming is applied for modeling decentralized decisions in which two decision makers make decisions successively. In this paper, we specifically address bi-level decision-making problems with budget constraint as an attractive feature in the context of enterprise-wide supply chain. We first describe the typical bi-level linear programming problem (BLLPP) and its optimal solution to the penalty function problem, and then, a cooperative decision-making problem in supply chain is modeled as BLLPP. A particle swarm optimization-based computational algorithm is designed to solve the problem, and the numerical example is presented to illustrate the proposed framework.
Vorheriger Artikel Incentive contracts of knowledge investment for cooperative innovation in project-based supply chain with double moral hazard
Nächster Artikel Uncertain Johnson–Schumacher growth model with imprecise observations and k-fold cross-validation test

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Metadaten
Titel
Bi-level programming problem in the supply chain and its solution algorithm
verfasst von
Haiyan Luo
Linzhong Liu
Xun Yang
Publikationsdatum
05.04.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 4/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-03930-7

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