Hybrid Genetic Algorithm and Variable Neighborhood Search for Dynamic Facility Layout Problem

Abstract

This paper presents a novel hybrid metaheuristic GA-VNS matching genetic algorithm (GA) and variable neighborhood search (VNS) to the dynamic facility layout problem (DFLP). The DFLP is a well-known NP hard problem which aims at assigning a set of facilities to a set of locations over a time planning horizon so that the total cost including material handling cost and rearrangement cost is minimized. The proposed hybrid approach in this paper elegantly integrates the exploitation ability of VNS and exploration ability of GA. To examine the performance of the proposed hybrid approach, a set of instance problems have been used from the literature. As demonstrated in the results, the GA-VNS is mighty of attaining high quality solution. Compared with some state-ofthe-art algorithms, our proposed hybrid approach is competitive.

A Research on Dynamic Facility Layout Problems

“…Uddin [42] suggested a noval hybrid meta-heuristic GA-VNS for DFLP where the population was divided into two parts as GA and VNS for better solutions. Liu et al [43] proposed Wang-landau (WL) sampling algorithm for DFLP.…”

A Multi-Agents System for Solving Facility Layout Problem: Application to Operating Theater

“…These methods used encoding and decoding schemes for solution representation to improve the swapping rearrangement of facilities within their meta-heuristic framework. Uddin [31] introduced a hybrid GA and VNS for dynamic FLP. To ensure a strong cooperation of GA and VNS, the population was split into two parts, where each part was assigned to a method considering a hybridizing coefficient to adjust the percentage of splitting population.…”