On the adoption of Metaheuristics for Solving 0-1 Knapsack Problems

Document Type

Conference Proceeding

Publication Date

1-1-2021

Abstract

0-1 knapsack problem is a classical Non-deterministic Polynomial Hard (NP-Hard) problem in combinatorial optimization. It has a wide range of applications in real life, such as the distribution of goods in logistics companies, capital calculation, storage, and distribution, etc. This paper studies the adoption of three meta-heuristic approaches for solving the 0-1 knapsack problem. A novel quantum-inspired Tabu Search (QTS) that combines a classical Tabu Search (TS) and Quantum-inspired Evolutionary Algorithm (QEA), Ant Colony swarm intelligence Algorithm (ACO), and Genetic Algorithm (GA) with augmented fitness function. Based on empirical analysis of computer simulations and comparative demonstrations, we show that applying such metaheuristic results in high efficiency in terms of the quality of obtained solutions, computational time, and robustness when dealing with the underlying 0-1 knapsack optimization problem.

Publication Title

Proceedings - International Symposium on Parallel Architectures, Algorithms and Programming, PAAP

First Page Number

56

Last Page Number

61

DOI

10.1109/PAAP54281.2021.9720471

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