Mathematical Modelling and an Effective Algorithm for Unidirectional Loop Layout Problem with Fixed Loading and Unloading Points

Reasonable positions of material loading and unloading points are the key factors to reduce material handling costs and improve material efficiency in manufacturing workshops. In response to the assumption of overlapping material handling points in current loop layout studies, this study proposes a unidirectional loop layout problem that considers the positions of material handling points between facilities. A mixed-integer linear programming model is constructed with the optimization objective of minimizing material handling costs. Recognizing the computational complexity of solving the problem, an adaptive hybrid algorithm of genetic algorithm and simulated annealing algorithm is proposed to obtain a better layout for the large-scale problem. For the problem characteristics, an efficient encoding and decoding strategy is designed to generate good initial solutions at the initial stage of the algorithm. The genetic algorithm is improved by combining adaptive crossover, adaptive mutation and nested simulated annealing algorithm, and a double threshold stopping criterion is used to remove the number of redundant cycles to improve the performance of the proposed algorithm. Finally, the proposed algorithm is applied to solve some benchmark instances, and the results are analysed to verify the efficiency and stability of the proposed algorithm. And the proposed algorithm is successfully applied to the security door production workshop to provide an improved layout scheme.