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Graduation Thesis from 2013
Kim, Min Geun
M.S. |
Scheduling algorithms for remanufacturing systems with parallel flow-shop-type reprocessing lines This study considers the operations scheduling problem in remanufacturing systems that consist of a single disassembly workstation, parallel flow-shop-type reprocessing lines and a single reassembly workstation. End-of-use/life products are separated into its components at the disassembly workstation, then each component is reprocessed at one of dedicated flow-shop-type reprocessing lines. Finally, the reprocessed components are reassembled into the remanufactured products at the reassembly workstation. The problem is to determine the sequence of products to be disassembled, the sequence of components to be reprocessed at each stage of flow-shop-type reprocessing lines and the sequence of products to be reassembled. The objective is to minimize the total flow time. To represent the problem mathematically,
an integer programming model is developed. Due to the complexity of the problem, we suggest two types of heuristics: (a) modified NEH heuristic; and iterated greedy algorithm. To show the performances of the heuristics, computational experiments were done on various test instances. The performances of various priority rules, including newly developed ones, are compared in a numerical example. |
Lee, Chul Won
M.S. |
A Capacity and Production Planning Model for Hybrid Production Systems with Manufacturing and Remanufacturing Facilities This study considers capacity and production planning in a hybrid system with two product supply channels, i.e., manufacturing facility that produces new products and remanufacturing facility that produces like-new products by reprocessing end-of-use/life products. The integrated problem is to determine capacity requirements and production quantities at both manufacturing and remanufacturing facilities to satisfy the demands over a given planning horizon. In particular, we consider
the budget constraint that limits the amount of capacity change costs required over the planning horizon. The objective is to minimize the total cost, i.e., sum of shutdown, production (setup and operation), inventory holding and subcontracting costs.
To represent the problem mathematically, a mixed integer programming model is suggested. Then, due to the problem complexity, we suggest two linear programming relaxation based heuristics, each of which fixes binary variables systematically using a certain procedure. Computational experiments were done on a number of test instances, and the test results are reported. |
Park, Jung Hyeon
M.S. |
Scheduling Algorithms for Job Shops with Job Families and Sequence-Dependent Setup Times: Minimizing the Total Family Flow Time This thesis considers job shop scheduling in which jobs are grouped into job families, but they are processed individually. As an extension of the previous study, we consider sequence-dependent setups, i.e., setup times depend on the type of job just completed and the next job to be processed. This type of job shop scheduling can be found in various manufacturing systems, especially in remanufacturing systems with disassembly, reprocessing and reassembly shops. In other words, the reprocessing shop can be regarded as the job shop with job families since it performs the operations required to bring parts or sub-assemblies disassembled back to like-new conditions before reassembling them. To minimize the deviations of the job completion times within each job family, we consider the objective of minimizing the total family flow time. Here, the family flow time implies the maximum among the completion times of the jobs within a job family. To describe the problem mathematically,
a mixed integer programming model is suggested, and then, due to the complexity of the problem, we suggest two iterated greedy algorithms with different neighborhood generation methods. Computational experiments were done using benchmark instances, and the results are reported. |
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