An improved pair-wise exchange heuristic for the dynamic plant layout problem

Abstract

Much of the research in facility layout has focused on static layouts where the material handling¯ow is assumed to be constant during the planning horizon. But in today's market-based, dynamic environment, layout rearrangement may be required during the planning horizon to maintain layout e ectiveness. A few algorithms have been proposed to solve this problem. They include dynamic programming and pair-wise exchange. In this paper we propose an improved dynamic pair-wise exchange heuristic based on a previous method published in this journal. Tests show that the proposed method is e ective and e cient.

Developing a method to generate semi-distributed layouts by genetic algorithm

“…Since in a dynamic layout the resource planning has a multi-period time horizon, at the beginning of each period in addition to variability in product demand and mix between two periods, a re-layout cost may be incurred (Balakrishnan et al 2000). In this approach, usually the objective is designing layouts with the aim of maximising material flow efficiency in each period besides balancing re-layout costs between periods Benjaafar 2002, 2005).…”

Proposition of two multiple criteria models applied to Dynamic Multi-objective Facility Layout Problem based on Ant Colony Optimization

“…The third heuristic (HAS III) adds the look-ahead/look-back strategy to the pair-wise exchange heuristic (local search). Their models had performed well with the two set of input data from Lacksonen and Enscore [5] and Balakrishnan and Cheng [7]. In summary, the main difference among the three algorithms is the local search/optimization─ HAS I uses a random descent pair-wise exchange heuristic; HAS II uses the Simulated Annealing (SA) as the local search; HAS III uses the random descent pair-wise exchange with the look-ahead/look-back strategy.…”

“…Urban proposed a steepdescent pair-wise interchange procedure combined with the concept of forecast windows [6]. Balakrishnan, Cheng and Conway [7] proposed an improvement to Urban's forecast windows procedure for solving the dynamic layout problem by complementing it with the backward method.…”

A clonal selection algorithm for dynamic facility layout problems

“…Balakrishnan et al [18] suggested some computationally efficient improvements to Urban's former pair-wise exchange procedure. Tests had shown that the improvements are worth to implement.…”