Path selection model and algorithm for emergency logistics management

Yuan, Yuan; Wang, Dingwei

doi:10.1016/j.cie.2008.09.033

Cited by 195 publications

(107 citation statements)

References 12 publications

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“…In DOM, many models are NP-hard Caunhye et al 2012); therefore, the algorithms for solving them are intensively studied (e.g., Hoyos et al 2015;Özdamar and Ertem 2015;Yuan and Wang 2009). For example, Wei and Kumar (2007) proposed an antcolony optimization method to solve the multi-commodity and vehicle dispatch problems that arise in disaster relief scenarios.…”

Section: Humanitarian or Disaster Operations Managementmentioning

confidence: 99%

Emergency logistics for wildfire suppression based on forecasted disaster evolution

2017

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This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces).

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Section: Humanitarian or Disaster Operations Managementmentioning

confidence: 99%

Emergency logistics for wildfire suppression based on forecasted disaster evolution

2017

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“…Formulations of evacuation planning problems range from network flow models Cova and Johnson, 2003;Hoppe & Tardos, 2007), cell-transmission-models (Chiu, Villabos, & Gautam, 2007), traffic assignment models , multiobjective path selection models (Yuan & Wang, 2009), and transshipment models (Hoppe and Tardos, 2000). Optimization-based solution algorithms include those based on Capacity Constrained Route Planning (Lu, Huang, & Shekhar, 2003;Lu, George & Shekhar, 2005;Lu, 2006), Flip High Flip Edge (Kim & Shekhar, 2005), contraflow network reconfiguration (Shekhar & Kim, 2006), and Multi-Ant Colony Systems (MACS) (Zong, Xiong, Fang, & Li, 2010).…”

Section: Evacuation Modelingmentioning

confidence: 99%

Heuristics for Solving Problem of Evacuating Non-Ambulatory People in a Short-Notice Disaster

Pico¹,

Tan²

2012

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to ABSTRACT (maximum 200 words)As Humanitarian Assistance and Disaster Relief (HADR) operations gain importance, a number of problems become evident. The time-sensitive problem of evacuating non-ambulatory people from a disaster area proves to be a challenging combinatorial optimization problem. The scope of the problem is defined by drawing analogies to similar vehicle routing problems that have been previously addressed. Based on the basic Max-Min Ant System (MMAS) algorithm modeled after the behavior of ants seeking food, potential solution approaches to this problem are enhanced to improve quality and efficiency by hybridizing features such as a best solution list, elite ants, ranked contribution system, and heuristic procedures during route construction. Using a Nearly-Orthogonal Latin Hypercubes (NOLH) experimental design, the algorithm parameters are tuned for best empirical performance for a range of test scenarios. SUBJECT TERMS HEURISTICS FOR SOLVING PROBLEM OF EVACUATING NON-AMBULATORY PEOPLE IN A SHORT-NOTICE DISASTER

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“…Moreover, they gave suggestions on how to select the most appropriate heuristic to solve different location problem instances. Metaheuristic of ant colony optimization was applied to solve the relief distribution problem (Yi and Kumar, 2007) and the path selection model (Yuan and Wang, 2009). The fuzzy clustering method was proposed by Sheu et al (2005) formulated to group affected areas and to associate the respective distribution priority with them.…”

Section: The Review Of Solution Algorithmmentioning

confidence: 99%

A Review of Relief Supply Chain Optimization

Manopiniwes¹,

Irohara²

2014

Industrial Engineering and Management Systems

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With a steep increase of the global disaster relief efforts around the world, the relief supply chain and humanitarian logistics play an important role to address this issue. A broad overview of operations research ranges from a principle or conceptual framework to analytical methodology and case study applied in this field. In this paper, we provide an overview of this challenging research area with emphasis on the corresponding optimization problems. The scope of this study begins with classification by the stage of the disaster lifecycle system. The characteristics of each optimization problem for the disaster supply chain are considered in detail as well as the logistics features. We found that the papers related to disaster relief can be grouped in three aspects in terms of logistics attributes: facility location, distribution model, and inventory model. Furthermore, the literature also analyzes objectives and solution algorithms proposed in each optimization model in order to discover insights, research gaps and findings. Finally, we offer future research directions based on our findings from the investigation of literature review.

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Path selection model and algorithm for emergency logistics management

Cited by 195 publications

References 12 publications

Emergency logistics for wildfire suppression based on forecasted disaster evolution

Emergency logistics for wildfire suppression based on forecasted disaster evolution

Heuristics for Solving Problem of Evacuating Non-Ambulatory People in a Short-Notice Disaster

A Review of Relief Supply Chain Optimization

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