An Improved Iterated Greedy Algorithm for Solving Collaborative Helicopter Rescue Routing Problem with Time Window and Limited Survival Time

Research on helicopter dispatching has received considerable attention, particularly in relation to post-disaster rescue operations. The survival chances of individuals trapped in emergency situations decrease as time passes, making timely helicopter dispatch crucial for successful rescue missions....

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Vydáno v:Algorithms Ročník 17; číslo 10; s. 431
Hlavní autoři: Cui, Xining, Yang, Kaidong, Wang, Xiaoqing, Duan, Peng
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.10.2024
Témata:
Acceptance criteria
Algorithms
Collaboration
collaborative helicopter rescue routing problem
Disasters
Effectiveness
Emergency procedures
Energy consumption
Evacuations & rescues
Greedy algorithms
Helicopter performance
Helicopters
Heuristic
improved iterated greedy algorithm
limited survival time
Literature reviews
Mathematical optimization
Methods
Neural networks
Optimization
post-disaster rescue
Rescue operations
Rescue work
Scheduling
Scheduling (Management)
Search and rescue missions
Search methods
Simulated annealing
Survival
time windows
Windows (intervals)
China
ISSN:1999-4893, 1999-4893
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Shrnutí:Research on helicopter dispatching has received considerable attention, particularly in relation to post-disaster rescue operations. The survival chances of individuals trapped in emergency situations decrease as time passes, making timely helicopter dispatch crucial for successful rescue missions. Therefore, this study investigates a collaborative helicopter rescue routing problem with time window and limited survival time constraints, solving it using an improved iterative greedy (IIG) algorithm. In the proposed algorithm, a heuristic initialization strategy is designed to generate an efficient and feasible initial solution. Then, a feasible-first destruction-construction strategy is applied to enhance the algorithm’s exploration ability. Next, a problem-specific local search strategy is developed to improve the algorithm’s local search effectiveness. In addition, the simulated annealing (SA) method is integrated as an acceptance criterion to avoid the algorithm from getting trapped in local optima. Finally, to evaluate the efficacy of the proposed IIG, 56 instances were generated based on Solomon instances and used for simulation tests. A comparative analysis was conducted against six efficient algorithms from the existing studies. The experimental results demonstrate that the proposed algorithm performs well in solving the post-disaster rescue helicopter routing problem.
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ISSN:1999-4893
1999-4893
DOI:10.3390/a17100431