Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory

Tribikram Pradhan, Akash Israni, Manish Sharma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper describes a hybrid algorithm to solve the 0-1 Knapsack Problem using the Genetic Algorithm combined with Rough Set Theory. The Knapsack problem is a combinatorial optimization problem where one has to maximize the benefit of objects in a knapsack without exceeding its capacity. There are other ways to solve this problem, namely Dynamic Programming and Greedy Method, but they are not very efficient. The complexity of Dynamic approach is of the order of O(n3) whereas the Greedy Method doesn't always converge to an optimum solution[2]. The Genetic Algorithm provides a way to solve the knapsack problem in linear time complexity[2]. The attribute reduction technique which incorporates Rough Set Theory finds the important genes, hence reducing the search space and ensures that the effective information will not be lost. The inclusion of Rough Set Theory in the Genetic Algorithm is able to improve its searching efficiency and quality.

Original languageEnglish
Title of host publicationProceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1120-1125
Number of pages6
ISBN (Electronic)9781479939145
DOIs
Publication statusPublished - 23-01-2015
Event2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014 - Ramanathapuram, Tamil Nadu, India
Duration: 08-05-201410-05-2014

Conference

Conference2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014
CountryIndia
CityRamanathapuram, Tamil Nadu
Period08-05-1410-05-14

Fingerprint

Rough set theory
Genetic algorithms
Combinatorial optimization
Dynamic programming
Genes

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering

Cite this

Pradhan, T., Israni, A., & Sharma, M. (2015). Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory. In Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014 (pp. 1120-1125). [7019272] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCCT.2014.7019272
Pradhan, Tribikram ; Israni, Akash ; Sharma, Manish. / Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory. Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1120-1125
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Pradhan, T, Israni, A & Sharma, M 2015, Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory. in Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014., 7019272, Institute of Electrical and Electronics Engineers Inc., pp. 1120-1125, 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014, Ramanathapuram, Tamil Nadu, India, 08-05-14. https://doi.org/10.1109/ICACCCT.2014.7019272

Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory. / Pradhan, Tribikram; Israni, Akash; Sharma, Manish.

Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1120-1125 7019272.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Pradhan T, Israni A, Sharma M. Solving the 0-1 Knapsack problem using genetic algorithm and rough set theory. In Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1120-1125. 7019272 https://doi.org/10.1109/ICACCCT.2014.7019272