Emergency transportation network design problem: Identification and evaluation of disaster response routes
TL;DR: In this paper, the authors proposed a branch-and-cut solution method to solve the problem of finding the optimal routes for emergency vehicles considering the length, the travel time and the number of paths as performance metrics of network vulnerability.
Abstract: Since disasters have considerable effects on transportation networks, the functionality of an emergency transportation network can play an important role in mitigation phase, especially in developing countries that sometimes suffer the sad experience of almost complete destruction of several cities. Transportation related disaster response activities typically include search and rescue, emergency medical care and fire-fighting trips. In this paper, the emergency transportation network design problem is proposed to determine the optimal network to perform emergency response trips with high priority in the aftermath of earthquakes. The problem has three objective functions designated to identify the optimal routes for emergency vehicles considering the length, the travel time and the number of paths as performance metrics of network vulnerability. A combined approach for considering the three objectives including weighted sum and lexicographic methods is used. The proposed model is solved using a branch-and-cut solution method. The suggested method is tested on the well-known Sioux-Falls network as well as on the real-world network of Tehran metropolis, Iran. Computational experiments are conducted to examine the effects of varying the maximum network length, and the relative weights of other objectives.
Citations
More filters
TL;DR: Estimating the amount of relief products through intensity measure is introduced through a mathematical model for initiation of humanitarian logistic operation plan and a genetic algorithm is proposed to solve the model.
32 citations
TL;DR: It is concluded that the EMS optimization models mainly aim at the shortest time, shortest distance, minimum cost, maximum satisfaction and fairness, etc, while the multi-objective model with complex constraints needs more efficient algorithms.
Abstract: In the emergency management of disruptions, efficient emergency material scheduling (EMS) is a key factor to save people's lives and reduce loss. Based on the literature of EMS and related areas in recent years, the research was summarized from two aspects of EMS optimization model and algorithms. It is concluded that the EMS optimization models mainly aim at the shortest time, shortest distance, minimum cost, maximum satisfaction and fairness, etc. The constraints usually include the quantity of supply depots, relief supply and vehicles, the types of commodities, the road network conditions, the budgets and the demand forecast of emergency materials. Multi-objective model is more complex and it usually considers more than one objective. To find the optimized solution, the multi-objective model with complex constraints needs more efficient algorithms. The existing algorithms, including mathematic algorithm and heuristic algorithm, have been categorized. For NP-hard (non-deterministic polynomial hard) problems, heuristic algorithms should be designed, which mainly include genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), etc. Based on the characteristics of the optimization model and various algorithms, appropriate algorithm or tools should be chosen and designed to obtain the optimized solution of EMS model. Finally, the development trends of EMS optimization model and algorithm in the future are proposed.
28 citations
TL;DR: Results evidence is obtained that the proposed methodology could help safety designers in the seismic emergency planning of urban paths by including the management of population's evacuation routes towards assembly points, the optimization of rescuers’ activities and the promotion of different priorities of interventions on building heritage.
Abstract: During seismic emergencies in historical urban scenarios, evacuation paths can suffer significant damages and modifications due to both extrinsic (i.e.: building facing the path) and intrinsic (i.e.: pavements state, the presence of underground lifelines or hypogeum) vulnerabilities. Such damages and modifications can hinder the population's evacuation and the first responders’ intervention, mainly because of paths' blockage or unavailability in emergency conditions. Paths’ safety is additionally affected by populations’ exposure conditions, also due to individuals’ motion in the post-earthquake environment. Hence, an analysis of factors influencing the seismic risk of evacuation paths and a consequent evaluation of their safety during the emergency are thus desirable. This work aims to offer a preliminary and quick holistic method for seismic risk assessment and damage level estimation of possible evacuation paths. Firstly, data about safety influencing factors (i.e.: path use and exposure; geometric features; physical-structural features; extrinsic vulnerability; seismic hazard) are collected, associated to related weights and organized in risk indexes according to three calculation approaches. Then, according to real-world data, a correlation about path risk-damage levels is proposed with the additional purpose to evaluate the method capabilities in describing post-earthquake scenarios. Obtained results evidence that the proposed methodology could help safety designers in the seismic emergency planning of urban paths (i.e.: by means of risk maps) by including the management of population's evacuation routes towards assembly points, the optimization of rescuers’ activities and the promotion of different priorities of interventions on building heritage.
25 citations
TL;DR: This research has introduced a mathematical model for humanitarian logistic applying the fact of redistribution of resources to minimize the total cost of whole operation and the total time for redistribution phase so as to response the emergency situation quickly.
25 citations
Cites background from "Emergency transportation network de..."
...[25] considering three main objective functions designed to identify the optimal routes for emergency vehicles considering the length, the travel time and the number of paths as performance metrics of network vulnerability in the emergency time of catastrophe....
[...]
01 Jan 2020
TL;DR: This research work has introduced a transportation plan considering the redistribution of resources from those areas which has already acquired relief and restored the normal condition to those areas still not being recovered from the effect of calamities.
Abstract: Unpredictable occurrence of any disaster emerges immeasurable demand in an affected society. Importance of immediate response in the aftermath of disaster is a crucial part of humanitarian logistic. Resource redistribution among the affected areas makes the optimal allocation in this chaotic situation. The research work has introduced a transportation plan considering the redistribution of resources from those areas which has already acquired relief and restored the normal condition to those areas still not being recovered from the effect of calamities. This research plan is developed to minimize the total cost of the relief operation as well as optimal allocation of the resources. The optimal allocation amidst the disruption of some resource storing points in the aftermath attack of disaster is also one of the key factors of the research. This research work has a great impact for decision-maker to derive an appropriate decision-making in such an anarchic situation of critical humanitarian supply chain. Due to the complexity of disaster, the model is considered in mixed uncertain environment. A numerical study is also performed to show the smooth functioning of the mathematical model assuming the uncertainty by trapezoidal neutrosophic number. Also, trapezoidal fuzzy number is implemented for uncertain parameters of the mathematical model and hereby compared with trapezoidal neutrosophic number.
23 citations
References
More filters
Book•
26 Sep 2011
TL;DR: This paper is concerned with the development of methods for dealing with the role of symbols in the interpretation of semantics.
Abstract: Preface. Acknowledgements. Notation and Symbols. Part I: Terminology and Theory. 1. Introduction. 2. Concepts. 3. Theoretical Background. Part II: Methods. 1. Introduction. 2. No-Preference Methods. 3. A Posteriori Methods. 4. A Priori Methods. 5. Interactive Methods. Part III: Related Issues. 1. Comparing Methods. 2. Software. 3. Graphical Illustration. 4. Future Directions. 5. Epilogue. References. Index.
4,976 citations
TL;DR: A survey of current continuous nonlinear multi-objective optimization concepts and methods finds that no single approach is superior and depends on the type of information provided in the problem, the user's preferences, the solution requirements, and the availability of software.
Abstract: A survey of current continuous nonlinear multi-objective optimization (MOO) concepts and methods is presented. It consolidates and relates seemingly different terminology and methods. The methods are divided into three major categories: methods with a priori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Genetic algorithms are surveyed as well. Commentary is provided on three fronts, concerning the advantages and pitfalls of individual methods, the different classes of methods, and the field of MOO as a whole. The Characteristics of the most significant methods are summarized. Conclusions are drawn that reflect often-neglected ideas and applicability to engineering problems. It is found that no single approach is superior. Rather, the selection of a specific method depends on the type of information that is provided in the problem, the user’s preferences, the solution requirements, and the availability of software.
4,263 citations
TL;DR: The significance of the new algorithm is that its computational upper bound increases only linearly with the value of K, so it is extremely efficient as compared with the algorithms proposed by Bock, Kantner, and Haynes and others.
Abstract: This paper presents an algorithm for finding the K loopless paths that have the shortest lengths from one node to another node in a network. The significance of the new algorithm is that its computational upper bound increases only linearly with the value of K. Consequently, in general, the new algorithm is extremely efficient as compared with the algorithms proposed by Bock, Kantner, and Haynes [2], Pollack [7], [8], Clarke, Krikorian, and Rausan [3], Sakarovitch [9] and others. This paper first reviews the algorithms presently available for finding the K shortest loopless paths in terms of the computational effort and memory addresses they require. This is followed by the presentation of the new algorithm and its justification. Finally, the efficiency of the new algorithm is examined and compared with that of other algorithms.
2,135 citations
TL;DR: The literature is surveyed to identify potential research directions in disaster operations, discuss relevant issues, and provide a starting point for interested researchers.
1,431 citations
TL;DR: A planning model that is to be integrated into a natural disaster logistics Decision Support System is developed that addresses the dynamic time-dependent transportation problem that needs to be solved repetitively at given time intervals during ongoing aid delivery.
Abstract: Logistics planning in emergency situations involves dispatching commodities (e.g., medical materials and personnel, specialised rescue equipment and rescue teams, food, etc.) to distribution centres in affected areas as soon as possible so that relief operations are accelerated. In this study, a planning model that is to be integrated into a natural disaster logistics Decision Support System is developed. The model addresses the dynamic time-dependent transportation problem that needs to be solved repetitively at given time intervals during ongoing aid delivery. The model regenerates plans incorporating new requests for aid materials, new supplies and transportation means that become available during the current planning time horizon. The plan indicates the optimal mixed pick up and delivery schedules for vehicles within the considered planning time horizon as well as the optimal quantities and types of loads picked up and delivered on these routes. In emergency logistics context, supply is available in limited quantities at the current time period and on specified future dates. Commodity demand is known with certainty at the current date, but can be forecasted for future dates. Unlike commercial environments, vehicles do not have to return to depots, because the next time the plan is re-generated, a node receiving commodities may become a depot or a former depot may have no supplies at all. As a result, there are no closed loop tours, and vehicles wait at their last stop until they receive the next order from the logistics coordination centre. Hence, dispatch orders for vehicles consist of sets of “broken” routes that are generated in response to time-dependent supply/demand. The mathematical model describes a setting that is considerably different than the conventional vehicle routing problem. In fact, the problem is a hybrid that integrates the multi-commodity network flow problem and the vehicle routing problem. In this setting, vehicles are also treated as commodities. The model is readily decomposed into two multi-commodity network flow problems, the first one being linear (for conventional commodities) and the second integer (for vehicle flows). In the solution approach, these sub-models are coupled with relaxed arc capacity constraints using Lagrangean relaxation. The convergence of the proposed algorithm is tested on small test instances as well as on an earthquake scenario of realistic size.
799 citations