报告题目：Hybrid Evolutionary Algorithms for Logistics Engineering（混合进化算法在物流工程中的应用）
报告人：Mitsuo Gen (玄光男) 教授，日本东京理科大学
时 间: 2015年4月24日(星期五)下午1:30-4:30
地 点: 杏运官网娱乐MBA304教室
联系人: 耿秀丽 xiuliforever@163.com
Abstract
Many combinatorial optimization problems (COP) in real world engineering systems impose on more complex issues, such as complex structure, nonlinear constraints, and multiple objectives to be handled simultaneously and make the problem intractable to the traditional approaches because of NP-hard COP. In order to develop solution algorithms that are in a sense "good," that is, whose computational time is small, or at least reasonable for NP-hard combinatorial problems met in practice, we have to consider the following issues: - Quality of solution, - Computational time and - Effectiveness of the nondominated solutions for multiobjective optimization problem (MOP).
Evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic such as genetic algorithm (GA), hybrid GA, and Multiobjective GA. EA is based on principles from evolution theory, and it is very powerful and broadly applicable stochastic search and optimization technique which is effective for solving various NP hard COP. This seminar will be introduced a thorough treatment of Genetic Algorithm, Hybridized GA (HGA), Multiobjective GA (MOGA) for solving various COP models in real world such as Designing SCM (Supply Chain Management) network and Reverse Logistic Models.
