Advances in stochastic programming and robust optimization for supply chain planning

Kannan Govindan, T. C.E. Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

This special issue addresses the advances in stochastic programming and robust optimization for supply chain planning by examining novel methods, practices, and opportunities. The articles present and analyze opportunities to improve supply chain planning through exploring various uncertainty situations and problems, sustainability assessment, vendor selection, risk mitigation, retail supply chain planning, and supply chain coordination. This editorial note summarizes the discussions on the stochastic models, algorithms, and methodologies developed for the evaluation and effective implementation of supply chain planning under various concerns. A dominant finding is that supply chain planning through the advancement of stochastic programming and robust optimization should be explored in a variety of ways and within different fields of applications.

Original languageEnglish
Pages (from-to)262-269
Number of pages8
JournalComputers and Operations Research
Volume100
DOIs
Publication statusPublished - Dec 2018

Keywords

  • Robust optimization
  • Stochastic programming
  • Supply chain planning
  • Uncertainties

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research

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