Petri Net Modeling and GA Based Scheduling for Assembly Industry
Date Issued
2004
Date
2004
Author(s)
Cheng, Hsing Hung
DOI
en-US
Abstract
In this thesis, we propose a new dispatching rule and a new sequencing rule for assembly industry in order to obtain a better overall schedule. In addition, we use a graphical and mathematical modeling tool – Colored-Timed Petri Nets (CTPN) to model the scheduling flow in an assembly plant. By use of the proposed CTPN model, we can simulate the production under some scheduling policies. Moreover, we apply Genetic Algorithm (GA) to help the underlying scheduling mechanism to obtain a near-optimal solution.
In the scheduling phase, two effective rules have been proposed in addition to usage of a number of well-known methods. For the better ones, some use static information (such as setup time, processing time, due date, etc…), whereas others use dynamic information (such as remaining processing time, queue length, equipment workload, etc …). However, the aforementioned two proposed rules consider both static and dynamic information. Both set of rules together are proposed to construct the schedule. Generally speaking, these rules hold two viewpoints, namely, one is to select equipments for work order (WO) and another is to select (work order) WO for equipment.
Given such mechanism, we further apply genetic algorithm (GA) based approach to search for the optimal combination of the set of rules. Our approach can be considered as taking the advantage of obtaining the next fittest WO selection when the current WO finishes its assembly operation. The hereby proposed approach not only can increase the solution space but also can help us to locate a satisfactory solution. Besides that, the CTPN based GA scheduler takes less computation time than a lot of other schedulers, so that the present scheduler can meet the need for a rapidly changing environment.
Subjects
基因演算法
斐氏網路
分派法則
製造排程
組裝工業
Petri Net
Sequencing Rule
Assembly
Scheduling
GA
Dispatching Rule
Type
thesis
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