Novel binary differential evolution algorithm for knapsack problems

DOI10.1016/j.ins.2020.07.013zbMath1475.90077OpenAlexW3043752008WikidataQ115445710 ScholiaQ115445710MaRDI QIDQ2053861

Daryl L. Essam, Ismail M. Ali, Kathryn Kasmarik

Publication date: 30 November 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.07.013

zbMATH Keywords

mapping methoddifferential evolutionfitness evaluationdiversity mechanismbinary knapsack problemsfitness repairing

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27)

Related Items (4)

A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints ⋮ Smallest covering regions and highest density regions for discrete distributions ⋮ An improved binary quantum-behaved particle swarm optimization algorithm for knapsack problems ⋮ An adaptive human learning optimization with enhanced exploration-exploitation balance

Cites Work

• A Modified Binary Particle Swarm Optimization for Knapsack Problems
• Pre-disaster investment decisions for strengthening a highway network
• Dynamic programming algorithms for the zero-one knapsack problem
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Dichotomous binary differential evolution for knapsack problems
• Infeasibility and structural bias in differential evolution
• Selection among ranked projects under segmentation, policy and logical constraints
• A Branch and Bound Method for the Multiconstraint Zero-One Knapsack Problem
• Differential Evolution for Binary Encoding

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