期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 184, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2021.115502
关键词
Case-based reasoning; Dimensionality reduction; Curse of dimensionality; Combinatorial optimization; Knapsack
The paper introduces a knowledge-based approach that combines case-based reasoning and operational research methodologies to solve repetitive combinatorial optimization problems, utilizing past experience to improve problem-solving efficiency, especially in cases where traditional schemes cannot solve the problem due to its large dimension.
This paper proposes a knowledge-based approach that combines case-based reasoning and operational research methodologies for solving repetitive combinatorial optimization problems. The novel approach makes use of past experience which is generally neglected in solving current optimization problems, and introduces this knowledge into operational research techniques for problem-solving, especially when the dimension of the problem is large and conventional schemes cannot solve it within a reasonable time limit. It greatly reduces the dimension of the problem and provides near-optimal solutions.
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