Optimization of different types of layout problems using meta heuristic algorithms

Abstract

In this research work, unique meta-heuristic methods like Improved Tabu Search (ITS), Improved Artificial Immune System (IAIS) and Simulated Annealing (SA) are implemented for solving linear, loop, single line, and multi-line of layout problems in flexible manufacturing systems. A software framework has been developed to identify an optimum layout sequence for various types of layout problems in flexible manufacturing systems to determine the optimal solutions. The comparison of the proposed ITS with other algorithms can be described by the character of the process carried out. The disorderly effects caused by the genetic operators like losing the best solution and substructures are avoided by the implementation of enhanced ITS which converges earlier with better results. It is evident from the research work that it confirms that new evolutionary technique namely, the ITS improves the loop layout problems for all the three layout problems namely i) with congestions and dimensions and also iii) without congestions. While the ITS to unequal area, single row layout problem in the case of same clearance problems are implemented, there is minimum improvement in results, but better results are obtained in different clearance. In addition, multi-row layout problems are discussed in flexible manufacturing environment. For the benchmark problem ITS produces better results when compared to similar algorithms that exist. Based on the industrial need of the real case study, the results determined by ITS provides lower transportation cost and improves production. For the hypothetical problem, the ITS produces better results than other algorithms. Further, future research can be carried out to enhance algorithms for different types of layout problems and mixed integer programming in cellular manufacturing system. newline