DocumentCode :
3381389
Title :
A genetic interval type-2 fuzzy logic based approach for operational resource planning
Author :
Mohamed, Amr ; Hagras, Hani ; Liret, Anne ; Shakya, Sunny ; Owusu, Gilbert
Author_Institution :
Comput. Intell. Centre, Univ. of Essex, Colchester, UK
fYear :
2013
fDate :
7-10 July 2013
Firstpage :
1
Lastpage :
8
Abstract :
Within service providing industries, one of the challenges facing resource planners is to match the demand for services by trying to utilize the available resources as best as possible. The problem faced by the operational resource planner is to build a refined plan of tasks to resources for each day in a manner that the plan can be directly dispatched to the distributed available engineering field force. In this paper, we will introduce a genetic hierarchical interval type-2 fuzzy logic based operational planner. We will present experiments which will show that the proposed system is able to produce more efficient plans when compared to the traditional crisp logic based algorithms which employ hill climbing heuristic based search techniques. We will show also that the proposed system outperforms the type-1 fuzzy logic based counterparts.
Keywords :
enterprise resource planning; fuzzy logic; fuzzy set theory; genetic algorithms; resource allocation; service industries; crisp logic based algorithm; engineering field force; genetic hierarchical interval type-2 fuzzy logic based operational planner; genetic interval type-2 fuzzy logic based approach; hill climbing heuristic based search technique; operational resource planning; resource utilization; service demand; service providing industries; task planning; Fuzzy logic; Fuzzy sets; Genetic algorithms; Genetics; Heuristic algorithms; Planning; Uncertainty; hierarchical fuzzy logic systems; operational resource planning; service providers; type-2 fuzzy logic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
Conference_Location :
Hyderabad
ISSN :
1098-7584
Print_ISBN :
978-1-4799-0020-6
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2013.6622341
Filename :
6622341
Link To Document :
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