Presentation 1997/5/22
Problem Solving based on the Control of Complexity : for Solving the Large Scale Traveling Salesman Problem
Seizaburo Niitsuma, Tsutomu Nakashima,
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Abstract(in English) This paper describes a meta-heuristics called an Inductive Algorithm, which is a problem-solving paradigm based on abstraction and analogical reasoning. The algorithm have been applied to combinatorial optimization prob-lems, for example, knapsack problems and traveling salesman problems (TSP) including hundreds of cities. The algorithm is developed which makes it possible to solve large scale TSPs consisting of scores of thousands of cities. To prevent a combinatorial explosion from happening, a vew point of control of problem complexity is introduced. The control is done by abstraction and setting scopes. The modified algolithm is applicable to TSP including 85,900 cities. Inductive Algorithm contains three kinds of parameters. This paper provides experimental results which show the algorithm to be stable for variations of parameters and give appropriate values for these parameters.
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Keyword(in English) meta-heuristics / inductive algorithm / abstraction / analogical reasoning / traveling salesman problem
Paper # AI97-4
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Committee AI
Conference Date 1997/5/22(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Problem Solving based on the Control of Complexity : for Solving the Large Scale Traveling Salesman Problem
Sub Title (in English)
Keyword(1) meta-heuristics
Keyword(2) inductive algorithm
Keyword(3) abstraction
Keyword(4) analogical reasoning
Keyword(5) traveling salesman problem
1st Author's Name Seizaburo Niitsuma
1st Author's Affiliation Department of Systems Engineering, Faculty of Engineering, Shizuoka University()
2nd Author's Name Tsutomu Nakashima
2nd Author's Affiliation Department of Systems Engineering, Faculty of Engineering, Shizuoka University
Date 1997/5/22
Paper # AI97-4
Volume (vol) vol.97
Number (no) 63
Page pp.pp.-
#Pages 8
Date of Issue