A tabu search approach for mixed-model parallel assembly line balancing problem (type II)

There are two types of assembly line balancing problems (ALBPs), which have received a great attention in the literature during the past four decades: types I and II. Both versions of ALBP are NP-hard and cannot be solved by exact methods. This paper presents an efficient tabu search (TS) metaheuristic approach for allocating tasks to balance the mixed-model production through the parallel assembly lines. Firstly, an initial solution is determined by a heuristic algorithm. Secondly, an optimum cycle time for each line in the mixed-model parallel assembly line (MMPAL) is calculated through the TS. The developed methodology, tabu search mixed-model parallel assembly line balancing (TMMPALB) model, is tested on test problems producing three and four products. Computational experiments show that the TMMPALB produces good enough solutions in case of MMPALs. The results of the proposed procedure improve cycle times of 77 test problems out of 87

Application of MATLAB to create initial solution for Tabu Search in parallel assembly lines balancing

In comparison with the exact mathematical methods, the heuristic models are different to provide solutions close to the optimal one, saving time of processing. With the appearance of the Tabu Search by Fred Glover in 1986, different applications have been arisen from the procedure to solve different problems for the classic problems of assembly line balancing and parallel mixed model assembly line. Here, an adaptation to an existing code appears which is applied to the problem of allocating and assigning mixed model tasks for the reconfiguration of distributed generation and balance with parallel assembly line. The model provides optimal or near optimal results in terms of results obtained from calculations compared to the other methods