Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems

DOI10.1016/j.cor.2010.02.004zbMath1231.90173OpenAlexW2002263103MaRDI QIDQ709108

Rosa Blanco, Francisco Ballestín

Publication date: 15 October 2010

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2010.02.004

zbMATH Keywords

heuristic algorithmsresource-constrained project schedulingmulti-objective

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

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Cites Work

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• Approximative solution methods for multiobjective combinatorial optimization. With discussion and a rejoinder by the authors.
• Bi-objective resource-constrained project scheduling with robustness and makespan criteria
• Experimental investigation of heuristics for resource-constrained project scheduling: an update
• A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty
• NP is as easy as detecting unique solutions
• Multiobjective network scheduling with efficient use of renewable and nonrenewable resources
• Multiple objective decision making - methods and applications. A state- of-the-art survey. In collaboration with Sudhakar R. Paidy and Kwangsun Yoon
• Interactive analysis of multiple-criteria project scheduling problems
• DSS for multiobjective project scheduling
• Resource-constrained project scheduling: A survey of recent developments.
• Project scheduling. A research handbook.
• Measuring the quality of discrete representations of efficient sets in multiple objective mathematical programming
• Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem
• Justification and RCPSP: a technique that pays
• Resource-constrained project scheduling: Notation, classification, models, and methods
• Using metaheuristics in multiobjective resource constrained project scheduling
• Scatter search for project scheduling with resource availability cost
• Scheduling of Project Networks by Job Assignment
• Pareto simulated annealing—a metaheuristic technique for multiple‐objective combinatorial optimization
• A self-adapting genetic algorithm for project scheduling under resource constraints
• Characterization and Generation of a General Class of Resource-Constrained Project Scheduling Problems