Ant Colony Optimization Model for Tsunamis Evacuation Routes

Forcael, Eric; González, Vicente A.; Orozco, Francisco; Vargas, Susana; Pantoja, Alejandro; Moscoso, Pablo

doi:10.1111/mice.12113

Cited by 79 publications

(46 citation statements)

References 35 publications

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“…Rahman and Mahmood [15] present an ant-based multi-agent system to provide feasible routes for building evacuation, considering the physical constrains of obstacles. Similarly, Forcael et al [2] apply the ant colony optimization model to find safe evacuation routes in the case of Tsunamis. Due to lack of consideration of the uncertainty and complexity of environments affected by hazards, these agent-based route planning systems have serious limitations in dealing with the uncertain information of the obstacles during disasters.…”

Section: Introductionmentioning

confidence: 99%

Path Planning for First Responders in the Presence of Moving Obstacles With Uncertain Boundaries

Wang

Zlatanova

Oosterom

2017

IEEE Trans. Intell. Transport. Syst.

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In this paper, we study the path planning for first responders in the presence of uncertain moving obstacles. To support the path planning, in our research we use hazard simulation to provide the predicted information of moving obstacles. A major problem in using hazard simulation is that the simulation results may involve uncertainty due to model errors or noise in the real measurements. To address this problem, we provide an approach to handle the uncertainty in the information of moving obstacles, and apply it to the case of toxic plumes. Our contribution consists of two parts: 1) a spatial data model that support representation of uncertain obstacles from hazard simulations and their influence on the road network; 2) a modified A* algorithm that can deal with the uncertainty and generate fast and safe routes passing though the obstacles. The experimental results show the routing capability of our approach and its potential for the application to real disasters.

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Section: Introductionmentioning

confidence: 99%

Path Planning for First Responders in the Presence of Moving Obstacles With Uncertain Boundaries

Wang

Zlatanova

Oosterom

2017

IEEE Trans. Intell. Transport. Syst.

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“…There are a few similar approaches, such as papers [35,36], but their objectives are different from ours. watches, etc.).…”

Section: Related Workmentioning

confidence: 99%

ANT: Agent Stigmergy-Based IoT-Network for Enhanced Tourist Mobility

López-Matencio¹,

Vales‐Alonso²,

Costa-Montenegro³

2017

Mobile Information Systems

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In this work, we propose ANT, a network of agents which exchange information in a stigmergy-based fashion. In ANT, each system's actor distributes pheromones as a way of indicating places' attractiveness, as well as for building a proper routing path to those sites. The goal of ANT is to improve the chances of discovering points of interest, as well as to reduce the time required for doing so. We have applied ANT to a tourist mobility scenario, where both people and things (events, restaurants, performances, etc.) participate. ANT has achieved notable success in this example case. We find that probability of discovering temporary events and dates improves by more than 35%, while the mean time employed to determine static point decreases by more than a third. We also introduce a mobile-based architecture which performs ANT tasks efficiently and easily for the user.

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“…This algorithm is very fast and known to find good solutions on a wide range of problems. A number of heuristic approaches such as genetic algorithm and ant colony algorithm are able to improve the performance of VRP [24,28,30,51,52]. However, these algorithms are not chosen in this article because they are really time consuming.…”

Section: Initialization Proceduresmentioning

confidence: 99%

Multi-objective inventory routing with uncertain demand using population-based metaheuristics

Yang¹,

Emmerich²,

Bäck³

et al. 2016

ICA

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Abstract. This article studies a tri-objective formulation of the inventory routing problem, extending the recently studied biobjective formulation. As compared to distance cost and inventory cost, which were discussed in previous work, it also considers stockout cost as a third objective. Demand is modeled as a Poisson random variable. State-of-the-art evolutionary multi-objective optimization algorithms and a new method based on swarm intelligence are used to compute approximation of the 3-D Pareto front. A bench-mark previously used in bi-objective inventory routing is extended by incorporating a uncertain demand model with an expected value that equals the average demand of the original benchmark. The results provide insights into the shape of the optimal trade-off surface. Based on this the dependences between different objectives are clarified and discussed. Moreover, the performances of the four different algorithmic methods are compared and due to the consistency in the results, it can be concluded that a near optimal approximation to the Pareto front can be found for problems of practically relevant size.

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Ant Colony Optimization Model for Tsunamis Evacuation Routes

Cited by 79 publications

References 35 publications

Path Planning for First Responders in the Presence of Moving Obstacles With Uncertain Boundaries

Path Planning for First Responders in the Presence of Moving Obstacles With Uncertain Boundaries

ANT: Agent Stigmergy-Based IoT-Network for Enhanced Tourist Mobility

Multi-objective inventory routing with uncertain demand using population-based metaheuristics

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