Hybrid particle swarm and differential evolution algorithm for solving multimode resource-constrained project scheduling problem

DOI10.1155/2015/923791zbMath1331.93067OpenAlexW2119315385WikidataQ59112476 ScholiaQ59112476MaRDI QIDQ5964346

Lie-Ping Zhang, Yu Zhang, Yingxiong Luo

Publication date: 29 February 2016

Published in: Journal of Control Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/923791

zbMATH Keywords

differential evolution (DE) algorithmmultimode resource-constrained project cheduling problem (MRCPSP)particle swarm optimization (PSO)project scheduling problem library (PSPLIB)

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Stochastic scheduling theory in operations research (90B36)

Related Items (1)

Multi‐mode resource‐constrained project scheduling using modified variable neighborhood search heuristic

Uses Software

• PSPLIB

Cites Work

• Using resource scarceness characteristics to solve the multi-mode resource-constrained project scheduling problem
• Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems
• Differential evolution for solving multi-mode resource-constrained project scheduling problems
• PSPLIB -- a project scheduling problem library
• An efficient particle swarm optimizer with application to man-day project scheduling problems
• Resource-constrained project scheduling: Notation, classification, models, and methods
• An improved differential evolution algorithm based on adaptive parameter
• A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems

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