Pseudo-parallel genetic algorithm in process mining

2012 ◽  
Author(s):  
Gang Xue ◽  
Xiaohu Ye ◽  
Jinwu Yang
Keyword(s):  
Genetic Algorithm ◽  
Process Mining ◽  
Parallel Genetic Algorithm ◽  
Pseudo Parallel Genetic Algorithm

scholarly journals A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Bailing Liu ◽  
Hui Chen ◽  
Yanhui Li ◽  
Xiang Liu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Computing Time ◽  
Single Type ◽  
Inventory Routing ◽  
Parallel Genetic Algorithm ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Stochastic Location ◽  
Pseudo Parallel Genetic Algorithm

Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.

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