Multi-Objective Differential Evolution (MODE) for optimization of supply chain planning and management

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

Many problems in the engineering domain involve more than one objective to be optimized simultaneously. The optimal solution to a multi-objective function results in a set of equally good solutions (Pareto optimal set), rather than a unique solution. Several entities are present in a typical supply chain problem. Each of these entities has its individual objectives. When all the objectives of supply chain are combined they work towards a common goal of increasing the profitability of an organization. The supply chain model is thus multi-objective in nature which involves several conflicting objectives. A three-stage supply chain problem (involving a network of supplier, plant and customer zones) is solved using Multi-Objective Differential Evolution (MODE) algorithm in this work. Three cases of objective functions are considered in this study. Pareto optimal solutions are obtained for each case. The results are compared with those reported using NSGA-II in the literature.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages2732-2739
Number of pages8
DOIs
Publication statusPublished - 2007
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: Sep 25 2007Sep 28 2007

Other

Other2007 IEEE Congress on Evolutionary Computation, CEC 2007
CountrySingapore
Period9/25/079/28/07

Fingerprint

Differential Evolution
Supply Chain
Supply chains
Planning
Optimization
Pareto Optimal Solution
Objective function
NSGA-II
Profitability
Differential Evolution Algorithm
Unique Solution
Customers
Optimal Solution
Engineering
Model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

Cite this

Babu, B. V., & Gujarathi, A. M. (2007). Multi-Objective Differential Evolution (MODE) for optimization of supply chain planning and management. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007 (pp. 2732-2739). [4424816] https://doi.org/10.1109/CEC.2007.4424816

Multi-Objective Differential Evolution (MODE) for optimization of supply chain planning and management. / Babu, B. V.; Gujarathi, Ashish M.

2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. p. 2732-2739 4424816.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Babu, BV & Gujarathi, AM 2007, Multi-Objective Differential Evolution (MODE) for optimization of supply chain planning and management. in 2007 IEEE Congress on Evolutionary Computation, CEC 2007., 4424816, pp. 2732-2739, 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Singapore, 9/25/07. https://doi.org/10.1109/CEC.2007.4424816
Babu, B. V. ; Gujarathi, Ashish M. / Multi-Objective Differential Evolution (MODE) for optimization of supply chain planning and management. 2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. pp. 2732-2739
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