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- Pei, Jun, et al.
(author)
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Minimizing the makespan for a serial-batching scheduling problem with arbitrary machine breakdown and dynamic job arrival
- 2016
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In: Advanced Manufacturing Technology. - : Springer Science and Business Media LLC. - 0885-5684. ; 86:9-12, s. 3315-3331
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Journal article (peer-reviewed)abstract
- Many dynamic events exist in real manufacturing systems, such as arbitrary machine breakdowns and dynamic job arrivals, which makes the scheduling problem even more complicated. In this paper, we address a serial-batching scheduling problem with the above dynamic events. Jobs need to be processed on the serial-batching machines of two manufacturers and then transported by vehicles to a customer for further processing. The objective of the scheduling problem is to minimize the makespan, and the problem is proved to be strongly NP-hard. Some structural properties and a lower bound of the problem are also proved or derived. On the basis of job arrival times, we divide the problem into two phases and propose different rules regarding these two phases. Based on these properties and rules, a heuristic algorithm is developed to solve the problem and its worst case performance is analyzed. The heuristic algorithm is tested on a large set of randomly generated problem instances, and the relative gaps between the found lower bound and the solutions of the proposed heuristic algorithm are reported. The experimental results illustrate the high efficiency and effectiveness of the proposed heuristic algorithm compared with other four classic approaches.
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| 4. |
- Pei, Jun, et al.
(author)
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Multi-Objective Optimization and Multi-Attribute Decision Making for a Novel Batch Scheduling Problem Based on Mould Capabilities
- 2015
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In: Optimization, Control, and Applications in the Information Age. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319185668 - 9783319185675 ; , s. 275-297
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Conference paper (peer-reviewed)abstract
- This chapter investigates a novel multi-objective model of a batch scheduling problem with constraint of the mould capability, and the objective is to minimize both the total completion time of the jobs and the total cost of the moulds. It is extremely difficult to obtain an optimal solution to this type of complex problems in a reasonable computational time. In view of this, this chapter presents a new multi-objective algorithm based on the features of Gravitational Search Algorithm to find Pareto optimal solutions for the given problem. In the proposed algorithm a novel Pareto frontier adjustment strategy is designed and proven to improve the convergence of solutions and increase convergence speed. We examined a set of test problems to validate the high efficiency of the proposed multi-objective gravitational search algorithm based on a variety of metrics. Finally, a multi-attribute decision making method is employed to determine the trade-off solutions derived from the Pareto optimal set and thus solve the problem optimally.
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- Pei, Jun, et al.
(author)
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Scheduling jobs on a single serial-batching machine with dynamic job arrivals and multiple job types
- 2016
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In: Annals of Mathematics and Artificial Intelligence. - : Springer Science and Business Media LLC. - 1012-2443 .- 1573-7470. ; 76:1-2, s. 215-228
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Journal article (peer-reviewed)abstract
- This paper investigates a scheduling model with certain co-existing features of serial-batching, dynamic job arrival, multi-types of job, and setup time. In this proposed model, the jobs of all types are first partitioned into serial batches, which are then processed on a single serial-batching machine with an independent constant setup time for each new batch. In order to solve this scheduling problem, we divide it into two phases based on job arrival times, and we also derive and prove certain constructive properties for these two phases. Relying on these properties, we develop a two-phase hybrid algorithm (TPHA). In addition, a valid lower bound of the problem is also derived. This is used to validate the quality of the proposed algorithm. Computational experiments, both with small- and large-scale problems, are performed in order to evaluate the performance of TPHA. The computational results indicate that TPHA outperforms seven other heuristic algorithms. For all test problems of different job sizes, the average gap percentage between the makespan, obtained using TPHA, and the lower bound does not exceed 5.41 %.
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- Pei, Jun, et al.
(author)
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Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine
- 2017
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In: Journal of Global Optimization. - : Springer. - 0925-5001 .- 1573-2916. ; 67:1-2, s. 251-262
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Journal article (peer-reviewed)abstract
- This paper deals with serial-batching scheduling problems with the effects of deterioration and learning, where time-dependent setup time is also considered. In the proposed scheduling models, all jobs are first partitioned into serial batches, and then all batches are processed on a single serial-batching machine. The actual job processing time is a function of its starting time and position. In addition, a setup time is required when a new batch is processed, and the setup time of the batches is time-dependent, i.e., it is a linear function of its starting time. Structural properties are derived for the problems of minimizing the makespan, the number of tardy jobs, and the maximum earliness. Then, three optimization algorithms are developed to solve them, respectively
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| 7. |
- Pei, Jun, et al.
(author)
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Single-machine serial-batching scheduling with a machine availability constraint, position-dependent processing time, and time-dependent set-up time
- 2017
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In: Optimization Letters. - : Springer. - 1862-4472 .- 1862-4480. ; 11:7, s. 1257-1271
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Journal article (peer-reviewed)abstract
- This article considers the single-machine serial-batching scheduling problem with a machine availability constraint, position-dependent processing time, and time-dependent set-up time. The objective of this problem is to make the decision of batching jobs and sequencing batches to minimize the makespan. To solve the problem, three cases of machine non-availability periods are considered, and the structural properties of the optimal solution are derived for each case. Based on these structural properties, an optimization algorithm is developed and an example is proposed to illustrate this algorithm
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