1. Multi-Objective ABC-NM Algorithm for Multi-Dimensional Combinatorial Optimization Problem.
- Author
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Rajeswari, Muniyan, Ramalingam, Rajakumar, Basheer, Shakila, Babu, Keerthi Samhitha, Rashid, Mamoon, and Saranya, Ramar
- Subjects
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BEES algorithm , *COMBINATORIAL optimization , *KNAPSACK problems , *ALGORITHMS , *PERFORMANCE standards - Abstract
This article addresses the problem of converting a single-objective combinatorial problem into a multi-objective one using the Pareto front approach. Although existing algorithms can identify the optimal solution in a multi-objective space, they fail to satisfy constraints while achieving optimal performance. To address this issue, we propose a multi-objective artificial bee colony optimization algorithm with a classical multi-objective theme called fitness sharing. This approach helps the convergence of the Pareto solution set towards a single optimal solution that satisfies multiple objectives. This article introduces multi-objective optimization with an example of a non-dominated sequencing technique and fitness sharing approach. The experimentation is carried out in MATLAB 2018a. In addition, we applied the proposed algorithm to two different real-time datasets, namely the knapsack problem and the nurse scheduling problem (NSP). The outcome of the proposed MBABC-NM algorithm is evaluated using standard performance indicators such as average distance, number of reference solutions (NRS), overall count of attained solutions (TNS), and overall non-dominated generation volume (ONGV). The results show that it outperforms other algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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