Solving an extended double row layout problem using multiobjective tabu search and linear programming

Facility layout problems have drawn much attention over the years, as evidenced by many different versions and formulations in the manufacturing context. This paper is motivated by semiconductor manufacturing, where the floor space is highly expensive (such as in a cleanroom environment) but there is also considerable material handling amongst machines. This is an integrated optimization task that considers both material movement and manufacturing area. Specifically, a new approach combining multiobjective tabu search with linear programming is proposed for an extended double row layout problem, in which the objective is to determine exact locations of machines in both rows to minimize material handling cost and layout area where material flows are asymmetric. First, a formulation of this layout problem is established. Second, an optimization framework is proposed that utilizes multiobjective tabu search and linear programming to determine a set of non-dominated solutions, which includes both sequences and positions of machines. This framework is applied to various manufacturing situations, and compared with an exact approach and a popular multiobjective genetic algorithm optimization algorithm. Experimental results show that the proposed approach is able to obtain sets of Pareto solutions that are far better than those obtained by the alternative approaches. Note to Practitioners-Manufacturing facility layouts are typically designed with the singular focus of promoting minimum-distance material flows, as material handling costs increase with travel distance. However, the square footage required by a layout also contributes to manufacturing costs, as is especially true in cleanroom environments typically found in semiconductor manufacturing. This paper proposes a methodology for determining a set of Pareto optimal solutions, highlighting the tradeoff between minimizing material flow cost versus facility size. We demonstrate this approach on a commonly used layout configuration, where two rows of machines are separated by an aisle. Despite the straightforward problem description, determining optimal solutions to this problem is challenging. Our approach is shown to work efficiently on problems of realistic size and provide implementable machine layouts.