Three-Stage Mixed Integer Robust Optimization Model Applied to Humanitarian Emergency Logistics by Considering Secondary Disasters

Du, Jianhui; Ji, Ying; Qu, Deqiang; Xiao-qing, WU; Yang, Dan

doi:10.1109/access.2020.3042980

Cited by 8 publications

(2 citation statements)

References 51 publications

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“…In [9], a hybrid ACO is proposed to solve the vehicle path problem by combining the ACO and the decentralized search algorithm and adding a new domain search algorithm to the decentralized search framework to improve the solution of the algorithm. e literature [10] combines the ant colony algorithm with the preservation algorithm and the exchange mechanism to improve the convergence speed of the algorithm, introduces the disaster operator, and adjusts the pheromone update formula to avoid the algorithm from falling into local optimum in the search process. Mahajan et al [11] studied the use of the ant colony algorithm to solve the vehicle path problem, adapt to the characteristics of the vehicle path problem, and made some changes to the ant colony algorithm; they introduced insertion and exchange operations after the ant colony algorithm finished a round of local pathfinding; and the customers served by each ant were subjected to random exchange and insertion operations according to the probability calculated by certain conditions so that the modified hybrid ant colony algorithm could get a better solution.…”

Section: Related Jobsmentioning

confidence: 99%

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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As an important historical and cultural heritage, rural red tourism sites have high historical, cultural, and social values. Moreover, rural red tourism sites are suitable for development and protection as tourism resources due to their unique landscape, architecture, culture, and art. In this paper, we propose a path generation model based on an ant colony algorithm to recommend the best path for tourists to visit rural red tourism sites. First, this paper investigates the modeling methods of path planning and multiobjective planning and their related solution algorithms to prepare for the establishment and solution of the tour path generation model for rural red tourism sites. By analyzing the problem description, this paper proposes the two model objectives of the shortest tour path and the highest total rating of the tourist attraction, and the model limitation of the total tour usage time, to model the model with a multiobjective planning approach. Then, by modifying the calculation of visibility and pheromone increments of the ant colony algorithm, the modified ant colony algorithm can take into account the two objectives of shortest path and highest total rating when constructing the path. Finally, this paper proposes to update the optimal path by using the number of ratings per unit path length as the update criterion of the optimal path.

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Section: Related Jobsmentioning

confidence: 99%

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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“…This reflects that there are some shortcomings and defects in somatic cells of emergency supplies in various countries suffering epidemics 1 , 2 . In the process of multi-scenario risk decision-making, the decision-maker has a certain prediction on the attribute value, which is completely rational expected utility, but the decision-maker, in reality, is finitely rational 3 , 4 .…”

Section: Introductionmentioning

confidence: 99%

Decision optimization of emergency material support based on blockchain under major public health emergencies

Wang

Fan

KunBao

2022

Sci Rep

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The work intends to relieve the pressure on the urban medical system and reduce the cross-infection of personnel in major public health emergencies. On the premise of an in-depth analysis of the utility risk entropy algorithm model and prospect theory, the decision-making of major health emergencies is proposed. Firstly, the utility risk entropy algorithm model is optimized, and the main decision-making members are subjected to utility perception according to the perceived utility values of different levels of risk, and the weights of decision-making members are calculated and revised according to the results of utility clustering. Secondly, the prospect theory is optimized. Taking the zero as the reference point to calculate the prospect value, and taking the maximization of the comprehensive prospect value as the objective to optimize the model, the comprehensive prospect value of each scheme is calculated and sorted. Finally, the proposed scheme is tested, and the test results show that in the optimal decision-making time of the scheme, the optimal decision-making time is 0 every day. When the epidemic situation is in the first cycle, the decision-making loss of the optimal scheme is 2.69, and the reduction ratio of the optimal scheme decision-making loss is 63.96%. When the epidemic situation is in the second cycle, the decision-making loss of the optimal scheme is 0.65, and the reduction ratio of the optimal scheme decision-making loss is 94.44%. When the epidemic situation is in the third cycle, the decision-making loss of the optimal scheme is 0.22, and the reduction ratio of the decision-making loss of the optimal scheme is 89.39%. The proposed scheme can improve the processing efficiency of major health emergencies and reduce the risk of accidents.

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Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul

Erişkin

Karataş

2022

Ann Oper Res

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Three-Stage Mixed Integer Robust Optimization Model Applied to Humanitarian Emergency Logistics by Considering Secondary Disasters

Cited by 8 publications

References 51 publications

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Decision optimization of emergency material support based on blockchain under major public health emergencies

Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul

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