Patvardhan, C., Bansal, Sulabh and Srivastav, Anand (2014) Balanced Quantum-Inspired Evolutionary Algorithm for Multiple Knapsack Problem. International Journal of Intelligent Systems and Applications, 6 (11). pp. 1-11. DOI 10.5815/ijisa.2014.11.01.

Full text not available from this repository.

Abstract

0/1 Multiple Knapsack Problem, a generalization of more popular 0/1 Knapsack Problem, is NP-hard and considered harder than simple Knapsack Problem. 0/1 Multiple Knapsack Problem has many applications in disciplines related to computer science and operations research. Quantum Inspired Evolutionary Algorithms (QIEAs), a subclass of Evolutionary algorithms, are considered effective to solve difficult problems particularly NP-hard combinatorial optimization problems. A hybrid QIEA is presented for multiple knapsack problem which incorporates several features for better balance between exploration and exploitation. The proposed QIEA, dubbed QIEA-MKP, provides significantly improved performance over simple QIEA from both the perspectives viz., the quality of solutions and computational effort required to reach the best solution. QIEA-MKP is also able to provide the solutions that are better than those obtained using a well known heuristic alone.

Document Type:	Article
Research affiliation:	Kiel University Kiel University > Kiel Marine Science OceanRep > The Future Ocean - Cluster of Excellence
Refereed:	Yes
Open Access Journal?:	No
Publisher:	Inderscience
Projects:	Future Ocean
Date Deposited:	29 Mar 2018 10:11
Last Modified:	23 Sep 2019 21:51
URI:	https://oceanrep.geomar.de/id/eprint/42517

Actions (login required)

View Item