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Graduation Thesis from 2012
Choi, Young Jae
M.S. |
Meta-heuristics for heterogeneous fixed fleet vehicle routing considering carbon emission and trading Heterogeneous fixed fleet vehicle routing, which is an extension of the classical capaci-tated vehicle routing problem, is the problem of determining a set of vehicle routes start-ing/ending at the depot, which satisfies customer demands and vehicle capacities for a given heterogeneous fleet of vehicles. As an extension of the previous studies, this study considers the problem with carbon emission and trading for the objective of minimizing the sum of variable operation costs and costs (benefits) associated with carbon emission (trading). The problem is formulated as a mixed integer programming model and then, due to the com-plexity of the problem, two types of meta-heuristics, simulated annealing and tabu search, are suggested to obtain good quality solutions within a reasonable amount of computation time. Computational experiments were done on the existing benchmark instances with a certain modification, and the results are reported. In particular, we show from the test instances that the total cost can be reduced due to benefits from carbon trading although carbon emission is additionally considered. |
Han, Hee Jong
M.S. |
Mathematical model and solution algorithm for selective disassembly sequencing with multiple target components and sequence-dependent setups This study considers the selective disassembly sequencing problem that determines the sequence of disassembly operations to obtain multiple target components of a used/end-of-life product for the purpose of repair, reuse, remanufacturing, disposal, etc. The problem is defined under the serial disassembly environment in which only one component is obtained at each disassembly operation. In particular, we consider sequence-dependent setup costs in which setup costs depend on the disassembly operation just completed and on the disassembly operation to be processed. The problem is represented as a disassembly precedence graph and a new integer programming model is suggested for the objective of minimizing the total disassembly cost. After we show that the problem is NP-hard, we suggest two types of heuristics: (a) branch and fathoming heuristic for small to medium sized instances; and (b) priority based heuristic for large-sized instances. A series of computational experiments were done on the effectiveness of the integer programming model and the performances of the two types of heuristics and the results are reported. In particular, to show the applicability of the mathematical model and the solution algorithms, a case study is reported on an end-of-life electronic calculator. |
Kim, Dong Hyun
M.S. |
Multi-period Disassembly Leveling and Scheduling: Mathematical Model and Solution Algorithm In this dissertation, we consider multi-period disassembly leveling and scheduling for multiple product types with parts commonality. Disassembly leveling, one of disassembly process planning decisions, is to determine disassembly structures that specify parts and subassemblies to be obtained from used or end-of-life products, and disassembly scheduling, one of disassembly operation decisions, is the problem of determining the timing and quantity of disassembling products and their subassemblies to satisfy the demands of their parts and/or subassemblies. As an extension of the previous studies, we consider the two problems, especially in a multi-period version, at the same time for multiple product types with parts commonality. In particular, we consider the generalized case that disassembly levels may be different for products of the same type and in different periods. To represent the integrated problem mathematically, an integer programming model is developed for the objective of minimizing the sum of disassembly setup, disassembly operation and inventory holding costs. Then, due to the problem complexity, we suggest a two-phase heuristic algorithm that consists of two phases: (a) constructing an initial solution using the priority based greedy heuristic; (b) and improvement. Finally, to show the performances the heuristic, computational tests were performed on a number of test instances and the results are reported. |
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