Knapsack Balancing via Multiobjectivization

In this paper, we address the aspect of knapsack balancing in the classic knapsack problem. Recognizing that excessive dispersion in the objective function or constraint coefficients of the optimal solution can be undesirable, we propose, when appropriate, to control this effect through problem multiobjectivization. By multiobjectivization, we mean the addition of one or more objective functions that aim to shift the original problem’s optimal solutions towards Pareto optimal solutions of the multiobjectivized problem, reducing the dispersion of the respective coefficients. We detail how the knapsack balance aspect can be incorporated into the standard knapsack problem model and demonstrate the functionality of this enriched model through illustrative examples.

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Publication Details

Journal
Applied Sciences
Published
2024-10-11
DOI
https://doi.org/10.3390/app14209236
Citations
2
Primary Topic
Optimization and Packing Problems
Type
article
Field-Weighted Citation Impact
0.70
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article

Knapsack Balancing via Multiobjectivization

Janusz Miroforidis, Ignacy Kaliszewski
2 citations
Applied Sciences
Optimization and Packing Problems
0.70
article

Knapsack Balancing via Multiobjectivization

Janusz Miroforidis, Ignacy Kaliszewski
article en
2 citations

Abstract

In this paper, we address the aspect of knapsack balancing in the classic knapsack problem. Recognizing that excessive dispersion in the objective function or constraint coefficients of the optimal solution can be undesirable, we propose, when appropriate, to control this effect through problem multiobjectivization. By multiobjectivization, we mean the addition of one or more objective functions that aim to shift the original problem’s optimal solutions towards Pareto optimal solutions of the multiobjectivized problem, reducing the dispersion of the respective coefficients. We detail how the knapsack balance aspect can be incorporated into the standard knapsack problem model and demonstrate the functionality of this enriched model through illustrative examples.

Applied SciencesVol. 14(20)
Systems Research Institute (PL), Polish Academy of Sciences (PL)
Openalex Percentile: Top 25%
Optimization and Packing Problems
0.70
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Knapsack Balancing via Multiobjectivization — Janusz Miroforidis, Ignacy Kaliszewski · Applied Sciences (2024) | TGRS Research Map | TGRS