Joint optimization of preventive maintenance and spare parts inventory using genetic algorithms and particle swarm optimization algorithm

2015 ◽  
Vol 6 (3) ◽  
pp. 248-258 ◽  
Author(s):  
Nishith Kumar Samal ◽  
Dilip Kumar Pratihar
Keyword(s):  
Genetic Algorithms ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Preventive Maintenance ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Spare Parts ◽  
Joint Optimization ◽  
Swarm Optimization ◽  
Spare Parts Inventory

Stochastic Optimization of the Repair Shops Location Problem Using Particle Swarm Optimization Algorithm

2015 ◽  
Author(s):  
Masoud Sharafi ◽  
Hamid Afshari ◽  
Tarek Y. ElMekkawy ◽  
Andrei V. Sleptchenko ◽  
Qingjin Peng
Keyword(s):  
Particle Swarm Optimization ◽  
Supply Chain ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Spare Parts ◽  
Repair Shop ◽  
Local Repair ◽  
Swarm Optimization ◽  
Number Of Customers

The optimization of facility location decisions is critical for the success of a supply chain in a market since it can contribute to long-term performance of the supply chain. In the last two decades, the number of research in this field has been growing to address more realistic problems such as incorporating uncertainties in repair time and demand. In this paper, a particle swarm optimization algorithm (PSO) is employed to locate repair shops in a stochastic environment. The problem aim is to decide about the location and the capacity of local repair shops as well as identifying the capacity of central repair shop to minimize total expected cost. It is assumed that customers select the closest local repair shop. In the local repair shops, services are available to repair customer’s broken items and a number of spare parts are stored to supply customers’ needs. Additionally, each repair shop is allowed to open some servers, depending on the number of customers, to serve its customers. If a stock-out happens, a customer should wait until the part is repaired in that shop. When a local repair shop is unable to repair a part, the part is sent to the central repair shop to be repaired. The central repair shop follows similar strategy for spare part inventory. The contribution of this paper is to employ a meta-heuristic solution approach based on particle swarm optimization for locating repair shops problem. In order to evaluate the performance of the employed solutions approach, its result is compared to other methods and differences are highlighted.

Multi-Scale Cooperative Mutation Particle Swarm Optimization Algorithm

2012 ◽  
Vol 23 (7) ◽  
pp. 1805-1815 ◽  
Author(s):  
Xin-Min TAO ◽  
Fu-Rong LIU ◽  
Yu LIU ◽  
Zhi-Jing TONG
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Scale
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