In this paper, Particle Swarm Optimization (PSO) integrated with Memetic Algorithm (MA) named as Modified Memetic Particle Swarm Optimization Algorithm (MMPSO) is applied to yield initial feasible solutions for scheduling of multi load AGVs for minimum travel and waiting time in the FMS. | Scheduling of multi load AGVs in FMS by modified memetic particle swarm optimization algorithm Journal of Project Management 3 2018 39 54 Contents lists available at GrowingScience Journal of Project Management homepage Scheduling of multi load AGVs in FMS by modified memetic particle swarm optimization algorithm . Chawlaa Arindam Kumar Chandab and Surjit Angrac a Researcher Mechanical Engineering Department NIT Kurukshetra India b Associate Professor Department of Mechanical and Automation Engineering G. B. Pant Engineering College Okhla Delhi India c Professor amp Head in the Department of Mechanical Engineering National Institute of Technology Kurukshetra India CHRONICLE ABSTRACT Article history Use of Automated guided vehicles AGVs is highly significant in Flexible Manufacturing Sys- Received July 5 2017 tem FMS in which material handling in form of jobs is performed from one work center to Received in revised format Au- another work center. A multifold increase in through put of FMS can be observed by application gust 28 2017 of multi load AGVs. In this paper Particle Swarm Optimization PSO integrated with Memetic Accepted September 27 2017 Available online Algorithm MA named as Modified Memetic Particle Swarm Optimization Algorithm September 27 2017 MMPSO is applied to yield initial feasible solutions for scheduling of multi load AGVs for Keywords minimum travel and waiting time in the FMS. The proposed MMPSO algorithm exhibits bal- Flexible Manufacturing System anced exploration and exploitation for global search method of standard Particle Swarm Opti- Memetic Algorithm mization PSO algorithm and local search method of Memetic Algorithm MA which further Modified Memetic Particle Swarm results into yield of efficient and effective initial feasible solutions for the multi load AGVs Optimization scheduling problem. Multi Load AGVs Particle Swarm Optimization Scheduling 2018 Growing Science Ltd. 1. Introduction Automated Guided .
