Bi-objective optimization for multi-floor facility layout problem with fixed inner configuration and room adjacency constraints. (March 2017)

• Record Type: Journal Article
• Authors: Che, Ada; Zhang, Yipei; Feng, Jianguang
• Is Part Of: Computers & industrial engineering. Volume 105(2017)
• Page Start: 265
• Page End: 276
• Publication Date: 2017-03
• Subjects: Facility layout problem -- Multi-floor -- Mixed integer linear programming -- Bi-objective optimization -- ε-constraint method; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.12.018
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A bi-objective model for multi-floor facility layout problem with fixed inner configuration. The aim is to minimize both the total material handling cost and total occupied room area. An exact ε-constraint method is employed to solve the model. Real-life and randomly generated instances are used to validate the approach. Abstract: The conventional facility layout problem (FLP) is concerned with arranging a number of interacting facilities, such as machines or departments, within a single-floor or multi-floor space to satisfy one or more objectives. In this paper, we devote ourselves to treating a novel bi-objective multi-floor FLP with fixed inner configuration and room adjacency constraints. In our problem, a given number of departments with required areas need to be arranged in a multi-floor building with fixed room configuration and the rooms of the same department should be adjacent to each other. In order to formulate the problem, a bi-objective mixed integer non-linear programming model is first proposed. The objective is to simultaneously minimize the total material handling cost among all the departments and the total occupied room area. The model is then linearized and further improved by determining the lower bound on the number of rooms occupied by each department. With the purpose of obtaining all Pareto optimal solutions, we employ an exact ε -constraint method to solve the model. Computational experiments on a real-life instance and randomly generated instances are conducted to validate the effectiveness of the proposed approach.