Evacuation planning using multiobjective evolutionary optimization approach

Saadatseresht, M.; Mansourian, Ali; Taleai, Mohammad

doi:10.1016/j.ejor.2008.07.032

Cited by 246 publications

(132 citation statements)

References 22 publications

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“…These kind of rules are used in practice, and are also presented in other optimization methods (see e.g. Saadatseresht et al (2009), wherein the shortest routes are chosen to lead evacuees from there origins to their destinations). The effectiveness of the different evacuations (both under assumption of full compliance is equal to, approximately: -75,000 (optimized instructions); -37,000 (instructions created by simple rules).…”

Section: An Evacuation With Optimized Instructions Compared With An Ementioning

confidence: 99%

“…Therefore, also methods that optimize traffic assignments or flows are included in the overview (as if they optimize instructions). In, for example, Miller-Hooks and Sorrel (2008) and Stepanov and Smith (2009), the route instructions are optimized, while in Saadatseresht et al (2009), the destination instructions are optimized. Both the route and the destination instructions are optimized in Liu et al (2006) and Ben-Tal et al (2009).…”

Section: Introductionmentioning

confidence: 99%

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A method to optimize evacuation instructions

et al. 2011

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In this paper, an optimization method is presented for instructions to evacuate by car the population of a region threatened by a hazard. By giving the optimized instructions to the evacuees, traffic conditions and, therefore, the evacuation efficiency are optimized. The instructions, containing a departure time, a safe destination, and a route, are created using an optimization method consisting of two phases: the generation of the search space and the algorithm AES + evacuation, a version of ant colony optimization. The main contributions of the proposed optimization method are the unique approach to generate the search space in which network degeneration is taken into consideration, the possibility to optimize instructions under the assumption of both full and partial compliance of the evacuees with the instructions, and the flexibility in the sense that the user of the method can define his or her own objective function and choose a suitable traffic simulation model. The paper contains a comprehensive case study. The case study shows that the effectiveness of the optimized instructions is more than doubled when compared with the effectiveness of instructions set up by straightforward rules (like evacuating to the nearest destination using the shortest route). Further, the case study shows that the number of arrivals under optimized, but possibly sub-optimal instructions is equal to at least 90% of the theoretical upper bound on this number of arrivals.

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Section: An Evacuation With Optimized Instructions Compared With An Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A method to optimize evacuation instructions

et al. 2011

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“…Constraint (10) indicates that the start point of any truck is known to be from what depot, while Constraint (11) is the constraint on the start point of helicopters. Constraints (12) and (13) guarantee that any vehicles (i.e., truck and helicopter) after serving any nodes must come back to the start point and the route is closed. Constraint (14) ensures that each vehicle (i.e., helicopter or truck) only serves one node (a point with healthy leading road) and consequently, Constraint (15) identi es that each vehicle (helicopter) serves only one unhealthy node (a ected point with damaged leading road).…”

Section: Notations and Sets Vmentioning

confidence: 99%

“…Saadatseresht et al [12] formulated an a ected population evacuation planning model in an earthquake disaster and solved it by multi-objective evolutionary optimization algorithm, NSGA-II. The related results showed the validity of the model.…”

Section: Introduction 1motivationmentioning

confidence: 99%

A cluster-based emergency vehicle routing problem in disaster with reliability

et al. 2017

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Abstract. In the event of natural disasters, relief distribution is the most challenging problem in emergency transportation. What is important in response to disaster is victims' relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. Therefore, this paper considers a problem using a three-stage approach. In the rst stage, pre-processing of model inputs is done through an Arti cial Neural Fuzzy Inference System (ANFIS) followed by investigating the safest route for each cluster using decision-making techniques and graph theory. In the second stage, a heterogeneous multi-depot multimode vehicle routing problem is formulated for minimizing the transportation time and maximizing the reliability. Finally, since the routing problem is NP-hard, 2 multi-objective meta-heuristic algorithms, namely, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Fire y Algorithm (MOFA), are proposed to obtain the optimal solution and their performances are compared through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions than NSGA-II does, and it performs well in terms of accuracy and solution time.

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“…For predictable disasters, which mainly are natural disasters such as hurricanes or floods, evacuation is required before disaster happens and the main objectives under this situation may be to minimise the system costs of evacuation and path risk, and to find the best location for rescue facilities (Kailiponi, 2010;Kongsomsaksakul et al, 2005;Li et al, 2012;Sherali et al, 1991). Locational aspects actually have a long tradition in emergency planning (Chang et al, 2012;Chu and Su, 2012;Daskin, 1982;Daskin and Stern, 1981;ReVelle, 1989;ReVelle and Snyder, 1995;Saadatseresht et al, 2009;Schilling et al, 1979Schilling et al, , 1980Toregas et al, 1971).…”

Section: Introductionmentioning

confidence: 99%

Design of evacuation plans for densely urbanised city centres

Coutinho-Rodrigues

Sousa

Natividade-Jesus

2016

Proceedings of the Institution of Civil Engineers - Municipal E

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The high population density and tightly packed nature of some city centres make emergency planning for these urban spaces especially important, given the potential for human loss in case of disaster. Historic and recent events have made emergency service planners particularly conscious of the need for preparing evacuation plans in advance. This paper discusses a methodological approach for assisting decision-makers in designing urban evacuation plans. The approach aims at quickly and safely moving the population away from the danger zone into shelters. The plans include determining the number and location of rescue facilities, as well as the paths that people should take from their building to their assigned shelter in case of an occurrence requiring evacuation. The approach is thus of the location-allocation-routing type, through the existing streets network, and takes into account the trade-offs among different aspects of evacuation actions that inevitably come up during the planning stage. All the steps of the procedure are discussed and systematised, along with computational and practical implementation issues, in the context of a case study -the design of evacuation plans for the historical centre of an old European city.

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Evacuation planning using multiobjective evolutionary optimization approach

Cited by 246 publications

References 22 publications

A method to optimize evacuation instructions

A method to optimize evacuation instructions

A cluster-based emergency vehicle routing problem in disaster with reliability

Design of evacuation plans for densely urbanised city centres

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