Study of Evolutionary Algorithms for Solving Facility Layout Problems

在许多工厂或工厂中，设施的位置和设施之间的配置与材料处理的有效性和其他操作问题有关。在本研究中，设施的空间位置决定问题被称为设施布局问题。在这个研究项目中，我们专注于操作和其他要求以及材料处理，并考虑设施之间的相邻偏好。通过使用邻接偏好，可以详细地考虑设施的优选配置。然而，由于邻接偏好项的满足被表示为二进制变量的0或1离散值，因此问题是复杂的。根据布局问题的规模大小，将布局问题分为几类.在设施数小于等于14的情况下，将该问题视为小规模问题，提出了一种基于分支定界法的求解算法。在数字的情况下， ...更多信息 BER大于14时，将该问题视为大规模问题，提出了基于模拟退火技术、遗传算法和禁忌搜索方法的进化算法。通过数值算例对这些算法进行了实验比较，得到了搜索效率和问题数据结构的信息。此外，为了解决超大规模的单层设施布局问题，提出了一种结合模拟退火和邻域搜索的新算法。通过在最近的个人计算机上使用我们的算法，对于在实际计算时间内不可能找到最优或半最优的大规模问题，它变得能够找到最优或优秀的解决方案。对于多层设施布局问题，在小问题的情况下提出了基于分支定界法的算法，在大问题的情况下考虑了对称布局等基于模拟退火技术的算法。少

In many plants or factories, the location of facilities and the configuration between facilities are related to the effectiveness of material handling and other operational issues. In this study, the problem of deciding spatial location of facilities is called as facility layout problem. In this research project, we focused on operational and other requirements as well as material handling, and considered adjacency preference between facilities. By using adjacency preference, preferable configuration of facilities can be considered minutely. However the problem is complicated because the satisfaction of adjacency preference items is represented to 0 or 1 discrete value of binary variables. We classified layout problems into some types with the problem size. In the case of the number of facilities less than or equal to 14, the problem is regarded as the small size problem, and we developed a new algorithm based on branch and bound method for solving such problems. In the case of the num … More ber is greater than 14, the problem is regarded as large size one, we developed evolutionary algorithms based on simulated annealing technique, genetic algorithms and tabu search method. We compared those algorithms by experiments using numerical examples, and got information of effectiveness of searching and data structure of problems. Moreover, far solving very large scale problem of single floor facility layout; a new algorithm combined simulated annealing and the original neighborhood search method is developed. By using our algorithm on recent personal computers, for large size problem that it is not possible to find the optimum or semi-optimum in practical computation time, it became to be able to find the optimum or the excellent solution. For solving multi floor facility layout problems, we proposed an algorithm based on branch and bound method in the case of small problem, and considering of symmetry layout and other algorithm based on simulated annealing technique to solve large problems. Less