Differential Evolution Algorithm for Constraint Joint Replenishment Problem

Author

Li, C.Y. ; Gao, J. ; Zhang, T.W. ; Wang, X.T.

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Univ. of Sci. & Technol., Harbin, China

fYear

2014

fDate

20-23 Dec. 2014

Firstpage

64

Lastpage

67

Abstract

We studied the joint replenishment problem with deterministic resource restriction. A differential evolution (DE) algorithm that uses indirect grouping strategy to solve constrained joint replenishment is presented. The procedure and structure of the DE algorithm is proposed. Extensive computational experiments are performed to compare the performances of the DE algorithm with results of genetic algorithm (GA) and heuristic algorithm CRAND. The experimental results indicate that the DE algorithm performs relative to CRAND and superior to GA.

Keywords

deterministic algorithms; genetic algorithms; inventory management; CRAND; DE algorithm; constrained joint replenishment; constraint joint replenishment problem; deterministic resource restriction; differential evolution algorithm; genetic algorithm; heuristic algorithm; indirect grouping strategy; Algorithm design and analysis; Decoding; Genetic algorithms; Heuristic algorithms; Joints; Mathematical model; Vectors; differential evolution; genetic algorithm; joint replenishment problem; resource constraint;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Generation Communication and Networking (FGCN), 2014 8th International Conference on

Conference_Location

Haikou

Print_ISBN

978-1-4799-7779-6

Type

conf

DOI

10.1109/FGCN.2014.23

Filename

7024345