期刊
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
卷 29, 期 10, 页码 771-800出版社
WILEY
DOI: 10.1111/mice.12111
关键词
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类别
资金
- Key Program of NSFC [70831005]
- 985 Program of Sichuan University Innovative Research Base for Economic Development and Management
- Research Foundation of Ministry of Education for the Doctoral Program of Higher Education of China [20130181110063]
- China Scholarship Council (CSC) [201206240138]
The aim of this article is to develop an antithetic method-based particle swarm optimization to solve a queuing network problem with fuzzy data for concrete transportation systems. The concrete transportation system at the Jinping-I Hydropower Project is considered the prototype and is extended to a generalized queuing network problem. The decision maker needs to allocate a limited number of vehicles and unloading equipment in multiple stages to the different queuing network transportation paths to improve construction efficiency by minimizing both the total operational costs and the construction duration. A multiple objective decision-making model is established which takes into account the constraints and the fuzzy data. To deal with the fuzzy variables in the model, a fuzzy expected value operator, which uses an optimistic-pessimistic index, is introduced to reflect the decision maker's attitude. The particular nature of this model requires the development of an antithetic method-based particle swarm optimization algorithm. Instead of using a traditional updating method, an antithetic particle-updating mechanism is designed to automatically control the particle-updating in the feasible solution space. Results and a sensitivity analysis for the Jinping-I Hydropower Project are presented to demonstrate the performance of our optimization method, which was proved to be very effective and efficient compared to the actual data from the project and other metaheuristic algorithms.
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