A Multi-Objective Optimization Model to theIntegrating Flexible Process Planning AndScheduling Based on Modified Particle SwarmOptimization Algorithm (MPSO)
نویسندگان
چکیده
Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm. Keywords—Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization
منابع مشابه
A Modified Discreet Particle Swarm Optimization for a Multi-level Emergency Supplies Distribution Network
Currently, the research of emergency supplies distribution and decision models mostly focus on deterministic models and exact algorithm. A few of studies have been done on the multi-level distribution network and matheuristic algorithm. In this paper, random processes theory is adopted to establish emergency supplies distribution and decision model for multi-level network. By analyzing the char...
متن کاملHybrid Multi-Objective Particle Swarm Optimization for Flexible Job Shop Scheduling Problem
Hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated annealing (SA) is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hy...
متن کاملA Multi-Objective Particle Swarm Optimization Algorithm for a Possibilistic Open Shop Problem to Minimize Weighted Mean Tardiness and Weighted Mean Completion Times
We consider an open shop scheduling problem. At first, a bi-objective possibilistic mixed-integer programming formulation is developed. The inherent uncertainty in processing times and due dates as fuzzy parameters, machine-dependent setup times and removal times are the special features of this model. The considered bi-objectives are to minimize the weighted mean tardiness and weighted mean co...
متن کاملOptimum allocation of Iranian oil and gas resources using multi-objective linear programming and particle swarm optimization in resistive economy conditions
This research presents a model for optimal allocation of Iranian oil and gas resources in sanction condition based on stochastic linear multi-objective programming. The general policies of the resistive economy include expanding exports of gas, electricity, petrochemical and petroleum products, expanding the strategic oil and gas reserves, increasing added value through completing the petroleum...
متن کاملDistribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm
Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before...
متن کامل