Integrated scheduling algorithm for multiple complex products with due date constraints

Aiming at the distributed integrated scheduling of complex products with tree structure, a memetic algorithm-based distributed integrated scheduling algorithm is proposed. Based on the framework of the memetic algorithm, the algorithm uses a distributed estimation algorithm for global search and performs a local search strategy based on the critical operation set for the current optimal solution obtained in each evolutionary generation. A bi-chain-based individual representation method is presented and a simple greedy insertion-based decoding method is given; two position-based probability models are built, which are used to describe the distribution of the operation priority and factory assignment, respectively. Based on the designed probability models, two learning-based updating mechanisms and an improved sampling method are given, which ensures that the population evolves towards a promising region. In order to enhance the searchability for the superior solutions, nine disturbance operators based on the critical operation set are presented. The parameters are determined by the design-of-experiment (DOE) test, and the effectiveness of the proposed algorithm is verified by comparative experiments.

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Integrated Scheduling Algorithm with Setup Time

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.213.226 ◽

2011 ◽

Vol 213 ◽

pp. 226-230

Author(s):

Zhi Qiang Xie ◽

Jing Yang ◽

Yu Zheng Teng ◽

Lan Lan

Keyword(s):

Time Complexity ◽

Scheduling Algorithm ◽

Research Result ◽

Setup Time ◽

Scheduling Problem ◽

Start Time ◽

Complex Products ◽

Integrated Scheduling

Aiming at the problem that there is no research result in the complex products processing and assemble integrated scheduling problem with setup time, this paper proposes strategy to resolve this problem. That is to determine scheduling sequence of procedures according to layer priority strategy, shorten time strategy and long path strategy. Then adopt algorithm of inserting setup time dynamically to determine the start time of procedures by scheduling sequence. As this algorithm avoids to move scheduled procedures many times after inserting setup time, the time complexity is only secondary. So this algorithm is simple and has high scheduling efficiency.

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Integrated scheduling algorithm based on the priority constraint table for complex products with tree structure

Advances in Mechanical Engineering ◽

10.1177/1687814020985206 ◽

2020 ◽

Vol 12 (12) ◽

pp. 168781402098520

Author(s):

Yilong Gao ◽

Zhiqiang Xie ◽

Xinyang Liu ◽

Wei Zhou ◽

Xu Yu

Keyword(s):

Scheduling Algorithm ◽

Tree Structure ◽

Initial Population ◽

Complex Products ◽

Dynamic Priority ◽

Integrated Scheduling ◽

Intelligent Optimization Algorithms ◽

Local Search Strategy ◽

Encoding Method ◽

Evolutionary Operators

Aiming at the existing intelligent optimization algorithms for solving the integrated scheduling problem of complex products with tree structure, there are problems of missing optimal solutions when designing encoding methods or generating infeasible offspring while designing evolutionary operators, an integrated scheduling algorithm based on the priority constraint table is proposed in this paper. A novel encoding method based on the dynamic priority constraint table is developed, which can guarantee the feasibility and completeness of the initial population individuals. For the legitimacy of the generated offspring individuals, two new different crossover and mutation methods are designed separately. The introduced evolutionary operators can avoid the detection and repairment of the infeasible individuals. An insertion-based greedy decoding method is also developed. In addition, based on the critical operations, a local search strategy is presented to enhance the search ability for the superior solutions. The feasibility and superiority of the proposed algorithm is verified by comparative experiments.

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A multi-shop integrated scheduling algorithm with fixed output constraint

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189721 ◽

2021 ◽

pp. 1-9

Author(s):

Yingchun Xia ◽

Zhiqiang Xie ◽

Yu Xin ◽

Xiaowei Zhang

Keyword(s):

Constraint Programming ◽

Programming Model ◽

Scheduling Algorithm ◽

Processing Parameters ◽

Scheduling Problem ◽

Integrated Scheduling ◽

Scheduling Scheme ◽

Wide Range ◽

Constraint Programming Model ◽

Output Constraint

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single shop to meet such a wide range of processing parameters. For the dynamic and fuzzy manufacturing characteristics of the products, not only the coordinated transport time of multiple shops but also the fact that the product has a designated output shop should be considered. In order to solve such Multi-shop Integrated Scheduling Problem with Fixed Output Constraint (MISP-FOC), a constraint programming model is developed to minimize the total tardiness, and then a Multi-shop Integrated Scheduling Algorithm (MISA) based on EGA (Enhanced Genetic Algorithm) and B&B (Branch and Bound) is proposed. MISA is a hybrid optimization method and consists of four parts. Firstly, to deal with the dynamic and fuzzy manufacturing characteristics, the dynamic production process is transformed into a series of time-continuous static scheduling problem according to the proposed dynamic rescheduling mechanism. Secondly, the pre-scheduling scheme is generated by the EGA at each event moment. Thirdly, the jobs in the pre-scheduling scheme are divided into three parts, namely, dispatched jobs, jobs to be dispatched, and jobs available for rescheduling, and at last, the B&B method is used to optimize the jobs available for rescheduling by utilizing the period when the dispatched jobs are in execution. Google OR-Tools is used to verify the proposed constraint programming model, and the experiment results show that the proposed algorithm is effective and feasible.

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