Title :
A hybrid Pareto-based algorithm for multi-objective resource allocation problem
Author :
Jun-qing Li ; Quan-ke Pan ; Kun Mao
Author_Institution :
State Key Lab. of Synthetic Autom. for Process Ind., Northeastern Univ., Shenyang, China
fDate :
May 31 2014-June 2 2014
Abstract :
This paper introduces a hybrid algorithm combining discrete harmony search (DHS) and iterated local search (ILS) for solving the multi-objective resource allocation problem (RAP). Two objectives are considered simultaneously, i.e. minimization of the overall cost and overall efficiency. The harmony search algorithm is used to conduct the global exploration task, while the iterated local search performs the exploitation work. In addition, an external Pareto archive set was introduced to memory the non-dominated solutions found so far. Experimental results on the well-known benchmarks verify the efficiency and effectiveness of the propose algorithm.
Keywords :
Pareto optimisation; iterative methods; minimisation; resource allocation; search problems; DHS; ILS; RAP; cost minimization; discrete harmony search algorithm; exploitation work; external Pareto archive set; global exploration task; hybrid Pareto-based algorithm; hybrid algorithm; iterated local search; multiobjective resource allocation problem; nondominated solutions; Algorithm design and analysis; Educational institutions; Optimization; Resource management; Search problems; Sociology; Statistics; Harmony search; Pareto archive set; multi-objective optimization; resource allocation problem;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852233