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Integration of process planning and ...
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Tan, Wei.
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Integration of process planning and scheduling functions: A mathematical programming approach.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Integration of process planning and scheduling functions: A mathematical programming approach./
作者:
Tan, Wei.
面頁冊數:
153 p.
附註:
Source: Dissertation Abstracts International, Volume: 59-08, Section: B, page: 4375.
Contained By:
Dissertation Abstracts International59-08B.
標題:
Engineering, Industrial. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9902875
ISBN:
0599000414
Integration of process planning and scheduling functions: A mathematical programming approach.
Tan, Wei.
Integration of process planning and scheduling functions: A mathematical programming approach.
- 153 p.
Source: Dissertation Abstracts International, Volume: 59-08, Section: B, page: 4375.
Thesis (Ph.D.)--University of Southern California, 1998.
Conventionally process planning and scheduling are two separate manufacturing functions. This type of separation often leads to, among other things, inflexible manufacturing scheduling and inefficient resource utilization. This dissertation proposes a systematic model to integrate process planning and scheduling functions. A series of mathematical programming models have been developed for modeling the integration problem. Encouraging results and valuable insights are obtained from extensive numerical experiments. The research covered in this dissertation shows that the models have strong promises for successful integration of process planning and scheduling functions in industrial settings.
ISBN: 0599000414Subjects--Topical Terms:
626639
Engineering, Industrial.
Integration of process planning and scheduling functions: A mathematical programming approach.
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Conventionally process planning and scheduling are two separate manufacturing functions. This type of separation often leads to, among other things, inflexible manufacturing scheduling and inefficient resource utilization. This dissertation proposes a systematic model to integrate process planning and scheduling functions. A series of mathematical programming models have been developed for modeling the integration problem. Encouraging results and valuable insights are obtained from extensive numerical experiments. The research covered in this dissertation shows that the models have strong promises for successful integration of process planning and scheduling functions in industrial settings.
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In the research, a polynomial mixed integer programming model has been developed. Then a scheme has been designed to linearize the polynomial model. Because of the size of the linearized model and its solution difficulty, a linear model LMIPM that is equivalent to the polynomial model has been developed. The LMIPM model uses far less variables and constraints than the linearized model. Experiments have shown that LMIPM model has outperformed other known approaches such as opportunistic scheduling and simulated annealing in terms of overall solution quality. In the later stage of this research, efforts have been devoted to improve the solution quality and speed of the LMIPM model. To address the needs for better quality and speed, an integrated solution model that links a heuristic with branch-and-bound has been developed. A tabu search algorithm has been developed as a fast heuristic to find an initial solution for a branch-and-bound procedure. Experiments have shown that the integrated solution model outperforms all other known approaches for each of the chosen 100 benchmark cases. This integrated solution model has further been evolved into a cooperative solver which establishes a two-way communications between a heuristic algorithm and an exact algorithm. Inside the cooperative solver, solutions from either algorithm may be passed to the other one as an initial solution. Preliminary studies have shown that the cooperative solver bears strong potential to be a highly efficient and high quality solver.
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