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Session:

Late Breaking Paper

Title:

Solving Multi-level Lot Sizing Problem with Memetic Algorithm Based on Refinement Procedure

 

 

Authors:

Hae-Joong Kim
Sung-Won Jung
Eoksu Sim
Jungsub Lee
Jinwoo Park

 

 

Abstract:

Production planning is a core function in manufacturing systems and is gaining even greater attention in supply chain environments where many mutually dependent and cooperative manufacturers are involved. Lot sizing is one of the most important and difficult problems in production planning. While optimal solution algorithms exist for this problem, only very small problems can be solved in a reasonable computation time because the problem is NP-hard. In this paper we present a meta-heuristic approach, which we call "Memetic Algorithm based on Refinement Procedure", to solve multi-level lot sizing (MLLS) problem. We use a local refinement procedure based on benchmarking to facilitate the solution search. The benchmark-based refinement procedure proposed by this study is also applicable to other problems where solutions are difficult to refine.

 

 

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