Supply Chain Multi-Product and Multi-Objective Bi-level Programming Under Fuzzy and Grey Uncertainty
The uncertain parameters in supply chain have different distribution styles. Some uncertain parameters containing fuzzy and grey twofold uncertain factors can be described with fuzzy grey variables. The supply chains planning model considering multi-product, multi-objective, and multi-factor constraints was presented under fuzzy and grey uncertainty. The first-level master model corresponds to optimizing the manufacturers profit under certain capital constraint. The second-level slave models correspond to simultaneously minimizing the cost for every type of supplied material. The proposed fuzzy grey simulation and grey simulation technology can generate input-output data to approximate the uncertain functions based on the credibility and chance measure of fuzzy grey variables. The hybrid optimal algorithm integrated the fuzzy grey simulation, grey simulation, and random simulation with bi-level genetic algorithm. This algorithm can optimize the uncertain programming problems. One numerical example is to illustrate the effectiveness of the model and algorithm.
Supply Chain Multi-product Multi-objective Bi-level Uncertain Programming Fuzzy Grey Simulation Genetic Algorithm
Dongbo Liu Dao Huang Yujuan Chen
Research Institute of Automation, East China University of Science & Technology Shanghai, 200237, Ch Research Institute of Automation, East China University of Science & Technology Shanghai, 200237, Ch College of Mechanical and Electronic Engineering, Shanghai Normal University Shanghai, 201418, China
国际会议
杭州
英文
924-928
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）