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Graduation Thesis from 2016
Rong Huang
M.S. |
Iterative algorithms for batching and scheduling to minimize the total tardiness in two-stage hybrid flow shops This study considers the batching and scheduling problem in two-stage hybrid flow shops in which each job with a distinct due-date is processed through two serial production stages, each of which has identical machines in parallel. Under the fundamental trade-off that large batch sizes may reduce setup costs and high machine utilization by requiring less frequent changeovers while small batch sizes may reduce job flow times and hence improve the relevant scheduling performances, the problem is to determine the batch composition, the allocation of batches to the parallel machines at each stage, and the sequence of the batches allocated to each machine for the objective of minimizing the total tardiness. A mixed integer programming model is proposed for the reduced problem in which the number of batches is given in advance, and then two iterative algorithms are developed in which the batching and scheduling sub-problems are solved repeatedly until good solution is obtained. To show the performances of the algorithms, computational experiments were done on various test instances, and the results are reported. |
Jong-Min Kim
M.S. |
Priority rule based scheduling to minimize total tardiness for remanufacturing systems with flow-shop-type reprocessing lines This study considers the operation scheduling problem in a remanufacturing system that separates end-of-use/life products into their components at a single disassembly workstation, then reprocesses each component at one of parallel flow-shop-type reprocessing lines and finally, reassembles the reprocessed components into remanufactured products at one of parallel reassembly workstations. The problem is to determine the sequence of products to be disassembled at the disassembly workstation, the sequence of components to be reprocessed at each workstation of the reprocessing lines and the allocation and sequence of products to be reassembled at reassembly workstations. As an extension of the previous study, we consider a due-date based objective, i.e. minimizing total tardiness. To represent the problem mathematically, a mixed integer programming model is proposed. |
Akmal Ulugov
M.S. |
Common due-date assignment and scheduling on a single machine with sequence-dependent setups and discretely controllable job processing times This study considers single machine common due-date assignment and scheduling with controllable processing times, which is the problem of determining the common due-date, the processing times and the sequence of jobs to be processed on a single machine. The controllable processing time of each job is considered in the discrete form in that it is determined by selecting one of its discretely available processing times. Moreover, the sequence-dependent setup, in which setup times depend on the type of job just completed and the job to be processed, is considered. A mixed integer programming model is proposed for the problem with the objective of minimizing the sum of earliness, tardiness, due-date assignment and job processing costs, where the job processing costs may be different for different available processing times. Then, due to the complexity of the problem, the two-stage heuristic algorithms are proposed in which an initial solution is obtained according to the positional weights and then it is improved by various interchange methods together with determining the job processing times. Computational experiments were done on various randomly generated test instances and the results are reported. |
Ga-Hyeon Joo
M.S. |
Heterogeneous period vehicle routing considering carbon emission: mathematical model and solution algorithm This study proposes a multi-period extension of heterogeneous fixed fleet vehicle routing with carbon emission, which is the problem of determining the routes of heterogeneous vehicles according to customer service combinations in each period of a planning horizon while satisfying customer demands and vehicle capacities. The objective is to minimize the sum of vehicle operation costs and carbon emission cost/benefit over the planning horizon, where the carbon emission cost/benefit is obtained from purchasing/selling the carbon emission right. To represent the problem mathematically, a mixed integer programming model is proposed. Then, a tabu search algorithm is developed that incorporates the characteristics of heterogeneous and period vehicle routing problems while considering the amount of carbon emission. Computational experiments were done on modified benchmark instances and randomly generated test instances, and the results show that the multi-period model proposed in this study gives better solutions than the existing single-period model in overall average. In particular, we show from the test results that the multi-period model reduces the amount of carbon emission more significantly than the single-period model without sacrificing the total cost. |
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