開發求解分群優化問題之蟻拓尋優法並求解教務單位時間表規劃問題
Date Issued
2003
Date
2003
Author(s)
DOI
912213E002115
Abstract
Object grouping optimization problems, known as NP-hard problems, are frequently
encountered in operation research areas and industrial fields. Traditionally, these problems are
modeled as set partitioning problems. In this research, viewpoint of group allocation for a set of
objects is adopted to construct mathematical models for object grouping optimization problems.
This research then focuses on developing an object grouping technique based ACO (Ant Colony
Optimization) method to solve this kind of problems. Design patterns of using ACO approaches to
solve object grouping optimization problems are discussed. General procedures are postulated for
further applications of solving this kind of problems.
To implement the proposed method, this research develops an ACO based software framework,
including core software classes, to solve object grouping optimization problems. These classes are
dedicated to using ACO techniques to solve object grouping problems. Based on this framework,
applications of solving exam timetabling problems and other grouping problems (including graph
coloring problems, node number balanced graph coloring problems, and bin packing problems)
are also implemented to verify the functionalities and expandability of the framework. The
framework this research proposed is a complete decision making tool for discrete optimization
problems.
Subjects
ant colony optimization
object grouping optimization
design pattern
Publisher
臺北市：國立臺灣大學工業工程學研究所
Type
report
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