| Title | Particle Swarm Optimization Algorithm with Variety Inertia Weights to Solve Unequal Area Facility Layout Problem |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Zhou, J.-L., Wang, J.-S., Zhang, Y.-X., Guo, Q.-S., Li, H., Lu, Y.-X. |
| Conference Name | 2020 Chinese Control And Decision Conference (CCDC) |
| Date Published | aug |
| Keywords | Analytical models, composability, compositionality, computational complexity, Conferences, convergence, dynamic inertia weight, facilities layout, Inertia Weight, Layout, nonlinear inertia weight, NP-hard problem, particle swarm optimisation, particle swarm optimization, particle swarm optimization algorithm, Production, PSO algorithm, pubcrawl, simulation, swarm intelligence, Swarm intelligence algorithm, UA-FLPP, unequal area facility layout problem, workshop area utilization |
| Abstract | The unequal area facility layout problem (UA-FLP) is to place some objects in a specified space according to certain requirements, which is a NP-hard problem in mathematics because of the complexity of its solution, the combination explosion and the complexity of engineering system. Particle swarm optimization (PSO) algorithm is a kind of swarm intelligence algorithm by simulating the predatory behavior of birds. Aiming at the minimization of material handling cost and the maximization of workshop area utilization, the optimization mathematical model of UA-FLPP is established, and it is solved by the particle swarm optimization (PSO) algorithm which simulates the design of birds' predation behavior. The improved PSO algorithm is constructed by using nonlinear inertia weight, dynamic inertia weight and other methods to solve static unequal area facility layout problem. The effectiveness of the proposed method is verified by simulation experiments. |
| DOI | 10.1109/CCDC49329.2020.9163977 |
| Citation Key | zhou_particle_2020 |
Particle Swarm Optimization Algorithm with Variety Inertia Weights to Solve Unequal Area Facility Layout Problem