کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
568111 1452170 2010 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
پیش نمایش صفحه اول مقاله
A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly
چکیده انگلیسی

The build-to-order supply chain (BOSC) model is a key operation model for providing services/products at present. This study focuses on performing the supply chain planning for the BOSC network. The planning is designed to integrate supplier selection, product assembly, as well as the logistic distribution system of the supply chain in order to meet market demands. With multiple suppliers and multiple customer needs, the assembly model can be divided into several sub-assembly steps by applicable sequence. Considering three evaluation criteria, namely costs, delivery time, and quality, a multi-objective optimization mathematical model is established for the BOSC planning in this study. The multi-objective problems usually have no unique optimal solution, and the Pareto genetic algorithm (PaGA) can find good trade-offs among all the objectives. Therefore, the PaGA is applied to find solutions for the mathematical model. In addition, regarding BOSC problems solving, this study proposes a modified Pareto genetic algorithm (mPaGA) to improve the solution quality through revision of crossover and mutation operations. After application and analysis of cases, mPaGA is found to be superior to traditional PaGA (tPaGA) in solution performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 41, Issues 7–8, July–August 2010, Pages 1011–1022
نویسندگان
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