| Summary: | 碩士 === 國立臺灣大學 === 資訊管理學研究所 === 98 === Recently, recovery management becomes an important issue around the world. In spite of all economical and environmental advantages of recovery, it is difficult to solve corresponding master planning (MP) problems as products are sequentially decomposed into multiple demand sources. Some network models are proposed before to solve such problems, but they are simple and with unrealistic assumptions.
In this study, a complete recovery supply chain model, which includes players like collectors, disassebmlers, shredders, reconditioners and garbage handlers, is proposed. Then, considering multiple product structures, multiple discrete planning periods and multiple demands, MP problems for recovery supply chains are solved to determine optimal transportation, processing, stocking, and garbage handling quantities of players.
To solve MP problems for recovery supply chains, a multiple-goal Mixed Integer Programming (MIP) model is proposed with two objectives. The first objective is to minimize the total delay cost. The second objective is to minimize the sum of processing cost, transportation cost, holding cost, setup cost and garbage handling cost given that the first one is minimized. Though the MIP model can obtain optimal solutions when problems are simple, the solving times grow exponentially with the increase of problem sizes. It may even fail to return feasible solutions when problems become extremely complex. To improve the effectiveness and efficiency of finding solutions, a heuristic algorithm, Recovery Process Master Planning Algorithm (RPMPA), is proposed.
The main process of RPMPA consists of three phases: preliminary works, demand grouping and sorting algorithm (DGSA), and the Recovery Process Path Selection Algorithm (RPPSA). For preliminary works, all multi-function nodes are split into single-function nodes and sub-networks of requested components are extracted. In DGSA, the sequence of demands is determined. Finally, in RPPSA, best disassembly paths and disassembly time schedules are decided for individual demands based on the sequence outputted by DGSA. To show the effectiveness and efficiency of RPMPA, a prototype is constructed and a scenario analysis is conducted.
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