An effective modified binary particle swarm optimization (mBPSO) algorithm for multi-objective resource allocation problem (MORAP)

DOI10.1016/j.amc.2013.06.039zbMath1329.90128OpenAlexW2006176137MaRDI QIDQ905291

Kun Fan, Weijia You, Yuan-Yuan Li

Publication date: 19 January 2016

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2013.06.039

zbMATH Keywords

algorithmPareto optimal solutionsbinary particle swarm optimization (BPSO)example simulationmulti-objective resource allocation problem (MORAP)

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Resource and cost allocation (including fair division, apportionment, etc.) (91B32)

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Cites Work

• Multiobjective resource allocation problem by multistage decision-based hybrid genetic algorithm
• An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP)
• An effective genetic algorithm approach to multiobjective resource allocation problems (MORAPs)
• Resource allocation during tests for optimally reliable software
• Optimal multiple-objective resource allocation using hybrid particle swarm optimization and adaptive resource bounds technique
• A new optimal approach for multiple optimisation objectives grid resource allocation and scheduling

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