Finding optimal dwell points for automated guided vehicles in general guide-path layouts

• Published in: International journal of production economics Vol. 170; pp. 850 - 861
• Main Authors: Ventura, José A., Pazhani, Subramanian, Mendoza, Abraham
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.12.2015; Elsevier Sequoia S.A
• Subjects: AGVS; Automated guided vehicle system; Automation; Dwell point location; Genetic algorithm; Genetic algorithms; Integer programming; Linear programming; Mathematical problems; Mixed integer linear programming model; Optimization algorithms; Response time; Studies; Vehicles; Automated guided vehicle system; Mixed integer linear programming model; Genetic algorithm; Dwell point location
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2015.03.007

The dwell points for idle vehicles in an automated guided vehicle (AGV) system determine the response times for pick-up requests and thus affect the performance of automated manufacturing systems. In this paper, we address the problem of optimally locating dwell points for a given number of AGVs in a general guide-path layout. Based on an optimality property, we propose new mixed integer linear programming (MILP) formulations for three versions of the problem: (i) minimizing the mean response time in the system, (ii) minimizing the maximum response time in the system, and (iii) minimizing the maximum response time in the system considering time restrictions on vehicle availability. Given that the computational time required to solve the MILP models significantly increases with the size of the guide-path network and number of available AGVs, we also develop a generic genetic algorithm (GA) that can be applied to all three versions of the problem. A computational study is carried out on the single-loop layout and two special cases of two-dimensional grid networks with the objectives of minimizing mean response time and minimizing the maximum response time. The results show that the proposed GA procedure can yield optimal or near optimal solutions in reasonable time. •In this paper we consider the optimal location of dwell points in AGV systems.•Mathematical models for three versions of the problem are formulated.•A genetic algorithm to solve all the three versions of the problem is developed.•A computational study is carried out on loop layouts and general grid networks.•Computational results show that the genetic algorithm is very efficient.