A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem

Parinaz Pourrahimian

doi:10.1007/s40092-017-0247-1

Abstract

Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average.

Highlights

Design of material handling system is among the key decision makings in designing any facility layout
To adjust the indices of the Genetic Algorithm (GA) and Tabu Search (TS) algorithms used in this study, the benchmark parameters used in the literature are adopted
The column AVG shows the average of best and worst solution for each algorithm and the column AVG IMPROV represents the improvement of objective function by applying proposed Memetic Algorithm (MA) against basic GA

Summary

Introduction

Design of material handling system is among the key decision makings in designing any facility layout. The cost associated with material handling is considerable; estimates average around 20–50% of total operational costs Tompkins et al (2010). A significant portion of labor cost is associated with material handling, moving or storing Groover (2007)

Methods

Results

Conclusion