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Pareto-Based Complete Local Search and Combined Timetabling for Multi-objective Job Shop Scheduling Problem with No-Wait Constraint 被引量:1
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作者 杨玉珍 顾幸生 《Journal of Donghua University(English Edition)》 EI CAS 2016年第4期601-609,624,共10页
Job shop scheduling has become the basis and core of advanced manufacturing technology. Various differences exist between academic research and practical production. The majority of previous researches on job shop sch... Job shop scheduling has become the basis and core of advanced manufacturing technology. Various differences exist between academic research and practical production. The majority of previous researches on job shop scheduling problem (JSSP)describe the basic production environment, which have a single objective and limited constraints. However,a practical process of production is characterized by having multiple objectives,no-wait constraint,and limited storage. Thus this research focused on multiobjective,no-wait JSSP. To analyze the problem,it was further divided into two sub-problems, namely, sequencing and timetabling. Hybrid non-order strategy and modified complete local search with memory were used to solve each problem individually. A Pareto-based strategy for performing fitness assessment was presented in this study. Various experiments on benchmark problems proved the feasibility and effectiveness of the proposed algorithm. 展开更多
关键词 Pareto scheduling scheduling constraints benchmark crossover fitness performing objectives sequencing
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Scheduling Optimization of Space Object Observations for Radar
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作者 Xiongjun Fu Liping Wu +1 位作者 Chengyan Zhang Min Xie 《Journal of Beijing Institute of Technology》 EI CAS 2018年第1期36-42,共7页
An optimizing method of observation scheduling based on time-division multiplexing is proposed in this paper,and its efficiency is verified by outdoor experiments. The initial observation scheduling is first obtained ... An optimizing method of observation scheduling based on time-division multiplexing is proposed in this paper,and its efficiency is verified by outdoor experiments. The initial observation scheduling is first obtained by using a semi-random search algorithm,and secondly the connection time pair( CTP) between adjacent objects is optimized by using a genetic algorithm. After obtaining these two parameters,the final observation scheduling can be obtained. According to pre-designed tracks between each adjacent objects in observation order,the seamless observation of neighboring targets is derived by automatically steering the antenna beam,so the observation efficiency is improved. 展开更多
关键词 space objects observation scheduling semi-random search genetic algorithm
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