Abstract
Facility layout problem is one of the most important problems in a huge range of industries and services organizations. Simultaneous study of some qualitative and quantitative parameters like closeness relationship between facilities, physical constraints such as input/output points and how to arrange facilities can play a key role to determine the facility layout. Considering these parameters can lead to reduce production costs, increase production capacity, and remove additional displacements. A two-stage approach is proposed to achieve these goals. In the first stage, a goal programming model is proposed to determine weights of the attributes based on the experts' opinions with different preference representation structures. Afterwards, the closeness ratings of the facilities are calculated using weights of attributes. In the second stage, an efficient layout is designed by determining facilities placement sequence, location of the next facility adjacent to the previous one, location of input/output points, and rectilinear feasible shortest path between facilities. Two meta-heuristic algorithms including particle swarm optimization and genetic algorithm are designed due to computational complexity. The objective function is to minimize the sum of products distance between facilities and closeness rating and also to minimize the dead space. A case study of an Auto Body Parts company is demonstrated to verify the efficiency of the proposed two-stage approach. Furthermore, in order to assess the performance of the proposed approach, a comparison is drawn between the proposed approach and five existing approaches in the literature to solve different problems by using the two meta-heuristic algorithms.
Highlights
The facility layout problem (FLP) is to find an efficient arrangement of most important assets of an organization, such as machines, cells, and departments on a planar site
Since 20-50% of the total operating cost of manufacturing company and 15-70% of the total cost of manufacturing of a product are attributed to MHC [1], the most significant factor to determine the efficiency of a layout is the material handling cost (MHC) [2]
Step 4: Determining scores of the alternatives The scores of the alternatives for this decision making problem are the values of the final closeness rating between each two facilities, which are calculated using Fuzzy Simple Additive Weighting (FSAW) [38] by considering weights of the attributes
Summary
The facility layout problem (FLP) is to find an efficient arrangement of most important assets of an organization, such as machines, cells, and departments on a planar site. Systems development and the complexity of the relationship between them, the different behaviors or insights of individuals (such as optimism and pessimism, risk-taking and risk-avoidance), different levels of their knowledge and experience due to environmental or geographical conditions, individual creativity and synergy of all-encompassing view of the group from different angles, and the perceived coping with the challenges by using individual judgments and decisions and their bias effects make it possible to use group decisions instead of individual ones in order to minimize the impacts of these biased judgments This judgment method for individuals can be defined by different preference representation structures. 1- A new method is presented to determine closeness ratings between facilities by using a set of experts’ opinions based on different preference representation structures. 3- Two meta-heuristic algorithms, a genetic algorithm (GA) and a particle swarm optimization (PSO), are designed to determine an efficient layout with respect to two objectives; the sum of products distance between facilities and the closeness rating, and dead space.
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