Meta-heuristic algorithms for resource Management in Crisis Based on OWA approach

In crisis management, Threat Evaluation (TE) and Resource Allocation (RA) are two key components. To build an automated system in this area after modelling Threat Evaluation and Resource Allocation processes, solving these models and finding the optimal solution are further important issues. In this...

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Published inApplied intelligence (Dordrecht, Netherlands) Vol. 51; no. 2; pp. 646 - 657
Main Authors Ghanbari, Abdolreza Asadi, Alaei, Hossein
Format Journal Article
LanguageEnglish
Published New York Springer US 01.02.2021
Springer Nature B.V
Subjects
Artificial Intelligence
Computer Science
Computing time
Decision trees
Evolutionary algorithms
Fire fighting
Fuzzy systems
Genetic algorithms
Heuristic methods
Machines
Management of crises
Manufacturing
Mechanical Engineering
Processes
Resource allocation
Resource management
Sorting algorithms
Threat evaluation
Dynamic resource allocation (DRA)
Multi-objective optimization (MOO)
Non-dominated sorting genetic algorithm-II (NSGA-II)
Maximum Bayesian entropy OWA (MBEOWA)
Strength Pareto evolutionary algorithm-II (SPEA-II)
Resource Management in Crisis (RMC)
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Summary:In crisis management, Threat Evaluation (TE) and Resource Allocation (RA) are two key components. To build an automated system in this area after modelling Threat Evaluation and Resource Allocation processes, solving these models and finding the optimal solution are further important issues. In this paper, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Strength Pareto Evolutionary Algorithms (SPEA-II) are employed to solve a multi-objective multi-stage Resource Allocation problem. These Algorithms have been compared using normalized values of the objectives by generational distance, spread, hyper-volume, cardinality and actual computational times. It is found that the non-dominated solutions obtained by SPEA-II are better than NSGA-II both in terms of convergence and diversity but at the expense of computational time. Here, the fuzzy inference systems and the decision tree have been used to conduct threat evaluation process. Finally, Ordered Weighted Averaging (OWA) with maximum Bayesian entropy method for determining the operator weights has been used to pick the final choice among optimal options. We plan to use the proposed method in this paper for crisis management in Iranian Red Crescent organization during fire fighting. Two real studies have been done and results have been presented.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-020-01808-y