Active Learning Method to Solve Bin Packing Problems

T. Lotfi and S.B. Shouraki (Iran)

Keywords

Combinatorial optimization, Reinforcement Learning, STAGE algorithm, Fuzzy algorithms.

Abstract

Previous researches have shown the success of using reinforcement learning in solving combinatorial optimization problems. The main idea of these methods is to learn (near) optimal evaluation function to improve local searches and find (near) optimal solutions. Stage algorithm introduced by Boyan & Moore, is one of the most important algorithm in this area. In the other hand fuzzy methods have been used in all fields of science to solve problems but still never used in combinatorial optimization problems. In this paper we focus on Bin Packing Problem. We introduce two basic fuzzy algorithms (ALM and IDS) and then solve our problem with these fuzzy algorithms. We run ALM and IDS algorithms on the set of data and find important inputs and extract narrow path. With this narrow path we investigate big valley structure for the set of its local minima. The result gives reasons for Stage's success in solving this problem. Then we use these algorithms in STAGE and will compare our results with previous works done with analytic methods to show how good and easy are these methods.

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