Stochastic Local Search for Solving Chance-Constrained Multi-Manned U-shaped Assembly Line Balancing Problem with Time and Space Constraints

Abstract

Mohammad Zakaraia1, Hegazy Zaher2, Naglaa Ragaa3 1PhD Candidate in Operations Research, faculty of graduate studies for statistical research, Cairo University, Egypt 2Professor Doctor in Mathematical statistics, faculty of graduate studies for statistical research, Cairo University, Egypt 3Associate Professor in Operations Research, faculty of graduate studies for statistical research, Cairo University, Egypt Abstract: The assembly line balancing problems have great importance in research and industry fields. They allow minimizing the learning aspects and guaranteeing a fixed number of products per day. This paper introduces a new problem that combines the multi-manned concept with the U-shaped lines with time and space constraints under uncertainty. The processing time of the tasks is considered as random variables with known means and variances. Therefore, chance-constraints appear in the cycle time constraints. In addition, each task has an associated area, where the assigned tasks per station are restricted by a total area. The proposed algorithm for solving the problem is a stochastic local search algorithm. The parameter levels of the proposed algorithm are optimized by the Taguchi method to cover the small, medium, and large-sized problems. Well-known benchmark problems have been adapted to cover the new model. The computational results showed the importance of the new problem and the efficiency of the proposed algorithm.