On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems

DOI10.1016/j.ins.2017.12.013zbMath1461.90040OpenAlexW2773606106MaRDI QIDQ781900

Shelvin Chand, Quang Huynh, Tapabrata Ray, Markus Wagner, Hemant Kumar Singh

Publication date: 20 July 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2017.12.013

zbMATH Keywords

evolutionary computationgenetic programmingresource-constrained project schedulinggeneration hyper-heuristicsheuristic evolution

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (3)

Generating decision rules for flexible capacity expansion problem through gene expression programming ⋮ Dynamic resource allocation and collaborative scheduling in R\&D and manufacturing processes of high-end equipment with budget constraint ⋮ A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problem

Uses Software

• PSPLIB

Cites Work

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• Scheduling subject to resource constraints: Classification and complexity
• Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation
• On the use of the complexity index as a measure of complexity in activity networks
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• An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem
• Justification and RCPSP: a technique that pays
• Resource-constrained project scheduling: Notation, classification, models, and methods
• Bidirectional planning: Improving priority rule-based heuristics for scheduling resource-constrained projects
• Project scheduling under limited resources. Models, methods, and applications
• A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem
• Critical-Path Planning and Scheduling: Mathematical Basis
• A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem

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