Title :
A New Differential Evolution for Discontinuous Optimization Problems
Author :
Zhang, Jihui ; Xu, Junqin
Author_Institution :
Qingdao Univ., Qingdao
Abstract :
This paper presents a stochastic method based on the differential evolution (DE) to address a wide range of discontinuous optimization problems such as scheduling and multi-item inventory control. DE is a novel evolutionary approach capable of handling non-differentiable, nonlinear and multi-modal objective functions. Previous studies have shown that DE is an efficient, effective and robust evolutionary algorithm, but it is not used to solve discontinuous problems. A novel solution encoding mechanism is used to handle discrete variables. In order to improve its search efficiency, a local search procedure is designed. Its performance is tested by some well known benchmark problems. Finally, it is used to solve a multi-item inventory problem which is a complicated mixed integer nonlinear optimization with complex constraints. Numerical results shown the useful of our method.
Keywords :
evolutionary computation; integer programming; inventory management; nonlinear programming; search problems; stochastic processes; differential evolutionary algorithm; discontinuous optimization problem; local search procedure; mixed integer nonlinear optimization; multi item inventory problem; multi modal objective function; nonlinear objective function; scheduling; stochastic method; Acceleration; Automation; Benchmark testing; Convergence; Genetic mutations; Model driven engineering; Optimization methods; Robustness; Scheduling; Stochastic processes;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.89