A Bottleneck Detection-Based Tabu Search Algorithm for the Buffer Allocation Problem in Manufacturing Systems

Buffer allocation is an important research issue in the design and optimization of manufacturing systems. One objective of buffer allocation is to maximize the throughput subject to the total buffer capacity in manufacturing systems. Previous studies have proposed many approaches to solve the buffer allocation problem, and tabu search has been proven to be effective in obtaining a near-optimal solution. To further improve the computational efficiency, this study proposes a bottleneck detection-based tabu search algorithm to efficiently solve the buffer allocation problem of manufacturing systems with sufficient solution quality. In particular, the tabu search algorithm integrated with diversification strategies is proposed to maintain satisfactory solution quality of the buffer allocation. The bottleneck detection cooperates with the variable neighborhood structure to search for proper locations for allocating buffers, decreasing the computational time of the buffer allocation. In addition, an existing throughput evaluation method is integrated with the proposed approach to evaluate neighborhood solutions by calculating the manufacturing system throughput. Numerical examples show that the proposed approach can obtain the near-optimal solution more efficiently than the simple tabu search and adaptive tabu search algorithms. This study improves the computational efficiency of buffer allocation in manufacturing systems without losing solution quality, contributing to efficient resource reconfiguration and process management.