Stochastic sequential supply chain management system: with a solution approach using the systematic sampling evolutionary method

Natnael Nigussie Goshu, Semu Mitiku Kassa

Research output: Contribution to journalArticlepeer-review

Abstract

Supply chain management describes a complex sequence of strategies implemented by multiple decision makers to transform raw materials into products and deliver to the market. Mathematical formulations of such problems involve hierarchical games with some form of stochastic properties in the problem definition. Such kind of mathematical problems are generally known to be NP-hard and are challenging to solve. This paper considers a general form of supply chain management problem with various forms of model formulations and analysis. Moreover, a solution approach based on a systematic sampling evolutionary method is also proposed to solve any form of such problem definitions to obtain a Stackelberg equilibrium or Stackelberg-Nash equilibrium solution. The convergence of the solution approach is shown. The reliability of the proposed method is checked. In addition to this, the algorithm is implemented on carefully constructed stochastic supply chain management problems and solutions to these problems are presented.

Original languageEnglish
Pages (from-to)264-288
Number of pages25
JournalInternational Journal of Business Performance and Supply Chain Modelling
Volume13
Issue number3
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management Science and Operations Research

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