A simulated annealing algorithm for unequal area dynamic facility layout problems with flexible bay structure

Abstract

In this article, we propose Simulated Annealing (SA) heuristic to solve Unequal Area Dynamic Facility Layout Problem (FBS) with Flexible Bay Structure (UA-DFLPs with FBS). The UA-DFLP with FBS is the problem of determining the facilities dimension and their location coordinates with flexible bays formation in the layout for various periods of the planning horizon. The UA-DFLP with FBS is more constrained than general UA-DFLP and it is an NP-complete problem. The proposed SA is tested with the available UA-DFLPs instances in the literature. The proposed SA heuristic has given new best solution or the same solution for FBS based problems as compared with the best-known reported in the UA-DFLPs with FBS literature. The proposed SA heuristic is also tested on standard UA-DFLPs used in non-FBS approaches. The SA heuristic solution is not significantly different from the best solution reported in the literature for non-FBS approaches. Equal area DFLP instances are also solved with the proposed SA and the results obtained are promising with the solutions reported in the literature. Hence the results obtained indicate that the proposed SA for UA-DFLP with FBS is effective and versatile for both equal and unequal area dynamic facility layout problems. The computational efficiency of the proposed SA heuristic is very much competitive as compared to other meta-heuristics computational timings reported in the literature.

Design of robust layout for unequal area dynamic facility layout problems with flexible bays structure

“…Unlike other metaheuristics, SA is simple to implement, and is computationally more efficient one, but it gives a single solution for each run. Due to the simplicity in implementation of SA, many researchers applied SA to facility layout problems (Tam, 1992;Baykasoglu and Gindy, 2001;McKendall et al, 2006;Pillai et al, 2011;Kulturel-Konak and Konak, 2015;Hunagund et al, 2018;Moslemipour, 2018). In the present study also, SA heuristic is applied to solve the proposed robust approach UA-DFLP with FBS formulation.…”

“…This MILP model is based on the strategy of adaptive approach and is solved using GA and GAMS software. Hunagund et al (2018) developed a simulated annealing solution method to solve the adaptive approachbased MILP model of UA-DFLPs with FBS of Mazinani et al (2013). Hunagund et al (2018) reported better solutions using their SA than the solution of GA approach of Mazinani et al (2013).…”

“…Hunagund et al (2018) developed a simulated annealing solution method to solve the adaptive approachbased MILP model of UA-DFLPs with FBS of Mazinani et al (2013). Hunagund et al (2018) reported better solutions using their SA than the solution of GA approach of Mazinani et al (2013). The drawback of adaptive approach is the rearrangement of facilities in various periods of the planning horizon which disrupts the operations.…”

“…These two problems are from Yang and Peters (1998). Kulturel- Konak and Konak (2015) and Hunagund et al (2018) in their study used the aspect ratio of two (a = 2) for these problems instead of fixed dimensions for the facilities. The present study also uses maximum aspect ratio of two (i.e.…”

Using eye-tracking into decision makers evaluation in evolutionary interactive UA-FLP algorithms

“…In recent years, meta-heuristic techniques have been extensively used for solving FLPs and, among them, genetic algorithms [2,19,23,35,44,49], simulated annealing [5,36,42], ant colony optimization [24,28,40,52], tabu search [8,30,33,54], particle swarm optimization [13,34], and coral reefs optimization [20].…”