A Comparative Study of Meta-Heuristic Optimization Algorithms for 0 – 1 Knapsack Problem: Some Initial Results

A Comparative Study of Meta-Heuristic Optimization Algorithms for 0 – 1 Knapsack Problem: Some Initial Results

In this paper, we present some initial results of several meta-heuristic optimization algorithms, namely, genetic algorithms, simulated annealing, branch and bound, dynamic programming, greedy search algorithm, and a hybrid genetic algorithm-simulated annealing for solving the 0-1 knapsack problems....

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Bibliographic Details
Main Authors: Absalom E. Ezugwu, Verosha Pillay, Divyan Hirasen, Kershen Sivanarain, Melvin Govender
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Knapsack problem
genetic algorithms
simulated annealing
branch and bound
dynamic programming
greedy search algorithm
Online Access:https://ieeexplore.ieee.org/document/8678633/

Internet

https://ieeexplore.ieee.org/document/8678633/

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