Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem

► We address a multi-objective project scheduling problem. ► Objectives: minimize project makespan and maximize effectiveness of human resources. ► To solve the problem, we propose a multi-objective hybrid algorithm. ► Integrating a simulated annealing algorithm and an evolutionary algorithm. ► The...

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Veröffentlicht in:	Expert systems with applications Jg. 40; H. 7; S. 2421 - 2434
Hauptverfasser:	Yannibelli, Virginia, Amandi, Analía
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.06.2013 Elsevier
Schlagworte:	Algorithms Applied sciences Computer science; control theory; systems Decision theory. Utility theory Evolutionary algorithms Exact sciences and technology Expert systems Inventory control, production control. Distribution Multi-objective evolutionary algorithm Multi-objective hybrid algorithm Multi-objective project scheduling Multi-objective simulated annealing algorithm Non-dominated solutions Operational research and scientific management Operational research. Management science Optimization Scheduling Scheduling, sequencing Searching Simulated annealing Software Software engineering Tradeoffs Non-dominated solutions Multi-objective project scheduling Multi-objective evolutionary algorithm Multi-objective hybrid algorithm Multi-objective simulated annealing algorithm Human capital Adaptive algorithm Software development Evolutionary algorithm Project management Priority Adaptability Multiobjective programming Staff management Scheduling Makespan Optimization Search algorithm Human activity Genetic algorithm Simulated annealing Problem solving Hybrid model Human resource management
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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