Hybrid genetic algorithm for multi-time period production/distribution planning

This paper proposes a new technique called spanning tree-based genetic algorithm (hst-GA) that is hybridized with the fuzzy logic controller (FLC) concept for auto-tuning the GA parameters and shows that the proposed method gives better results.

Abstract

In this paper, we deal with a production/distribution problem to determine an efficient integration of production, distribution and inventory system so that products are produced and distributed at the right quantities, to the right customers, and at the right time, in order to minimize system wide costs while satisfying all demand required. This problem can be viewed as an optimization model that integrates facility location decisions, distribution costs, and inventory management for multi-products and multi-time periods. To solve the problem, we propose a new technique called spanning tree-based genetic algorithm (hst-GA). In order to improve its efficiency, the proposed method is hybridized with the fuzzy logic controller (FLC) concept for auto-tuning the GA parameters. The proposed method is compared with traditional spanning tree-based genetic algorithm approach. This comparison shows that the proposed method gives better results.