An Immune Particle Swarm Optimization Method for Permutation Flow Shop Scheduling Problem
نویسندگان
چکیده
Permutation Flow Shop Scheduling Problem (PFSP) is a complex combinatorial optimization problem with strong engineering background. To solve the PFSP with makespan criterions, an immune particle swarm optimization (IPSO) algorithm was proposed. The initial solution of the algorithm is generated by the famous heuristic NEH algorithm, it was used to initialize the particle of global extreme values. Then we add a Dynamic Disturbance Term (DDT) in the velocity updating formulation of the particle, it used to prevent optimizing course from trapping the local minimum. Density and Immune Selection mechanism of Immune algorithm (IA) are used in the iterative process to select the optimal particle through the choice probability equation. The vaccination and memory operation to guide the global optimization process. At last, computational results show that the IPSO algorithm is effective robust and has a high performance. Key-Words: Permutation Flow Shop Scheduling; Particle Swarm Optimization Algorithm; Immune Algorithm; Makespan
منابع مشابه
Particle swarm optimization for minimizing total earliness/tardiness costs of two-stage assembly flowshop scheduling problem in a batched delivery system
This paper considers a two-stage assembly flow shop scheduling problem. When all parts of each product are completed in the first stage, they are assembled into a final product on an assembly machine in the second stage. In order to reduce the delivery cost, completed products can be held until completion of some other products to be delivered in a same batch. The proposed problem addresses sch...
متن کاملA New Cooperative Particle Swarm Optimizer and its Application in Permutation Flow Shop Scheduling Problem
In this study, a new variant of Particle Swarm Optimization, Electoral Cooperative PSO (ECPSO), is presented and applied into solving the Permutation Flow Shop Scheduling Problem (PFSSP). Firstly, an electoral swarm is generated by the voting of primitive sub-swarms and also participates in evolution of swarm, whose particle candidates come from primitive sub-swarms with variable votes from the...
متن کاملSolving Permutation Flow Shop Scheduling Problem with a Cooperative Multi-swarm PSO Algorithm ⋆
In this paper, an Electoral Cooperative Particle Swarm Optimization (ECPSO) based on several subswarms is presented to solving the Permutation Flow Shop Scheduling Problem (PFSSP). In the proposed algorithm, several strategies are employed to avoid falling into local optimum, improve the diversity and achieve better solution. Firstly, a electoral swarm is generated by the voting of primitive su...
متن کاملA Niche Sharing Scheme-based Co-evolutionary Particle Swarm Optimization Algorithm for Flow Shop Scheduling Problem
By taking advantage of niche sharing scheme,we propose a novel co-evolutionary particle swarm optimization algorithm (NCPSO) to solve permutation flow shop scheduling problem. As the core of this algorithm, niche sharing scheme maximizes the diversity of population and hence improves the quality of individuals. To evaluate the performance of the proposed algorithm, we have use eight Taillard in...
متن کاملA Two-Phase Hybrid Particle Swarm Optimization Algorithm for Solving Permutation Flow-Shop Scheduling Problem
In this paper, a two-phase hybrid particle swarm optimization algorithm (PRHPSO) is proposed for the permutation flow-shop scheduling problem (PFSP) with the minimizing makespan measure. The smallest position value (SPV) rule is used for encoding the particles that enable PSO for suitable PFSP, and the NEH and Tabu search algorithms are used for initializing the particles. In the first phase, t...
متن کامل