Meta-heuristic algorithms for solving a fuzzy single-period problem

Authors:
Ata Allah Taleizadeh;Farnaz Barzinpour;Hui-Ming Wee
Affiliations:
Department of Industrial Engineering, Iran University of Science and Technology, Iran;Department of Industrial Engineering, Iran University of Science and Technology, Iran;Department of Industrial & Systems Engineering, Chung Yuan Christian University, 32023 Chungli, Taiwan
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2011

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Abstract

Single-period problem (SPP) is a classical stochastic inventory model that has become very popular recently. In this research, we developed a SPP with fuzzy environment. The demand of each product is considered as LR-fuzzy variables (ranking fuzzy numbers based on the left and right deviation degrees), and multiple constraints (including service level, batch order, budget, space and upper limit for each order). The aim of this paper is to maximize the total expected profit under incremental discount strategy. Five hybrid intelligent algorithms based on fuzzy simulation (FS) and meta-heuristic methods are presented; they are bees colony optimization (BCO), harmony search (HS), particle swarm optimization (PSO), genetic algorithm (GA) and simulated annealing (SA). Three numerical examples are presented to illustrate the performance of the algorithms. Our study shows that the BCO-FS hybrid method performs better than the HS-FS, GA-FS, PSO-FS, and SA-FS hybrid methods.