An agent-based Decision Support System for resources' scheduling in Emergency Supply Chains

Othman, Sarah Ben; Zgaya, Hayfa; Dotoli, Mariagrazia; Hammadi, Slim

doi:10.1016/j.conengprac.2016.11.014

Cited by 49 publications

(27 citation statements)

References 32 publications

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“…During the Bird Flu and SARS in China, resource allocation was far beyond the capacity of local resource management, causing shortages of medical substances and food supply [42]. Timely and effective allocation and transportation of emergency resources can reduce losses caused by public crises [43]. As time, quantity and quality of the resources are the key limitation factors, emergency managers do have to find an optimal schedule for assigning resources to the affected areas [44].…”

Section: Crisis Management Literaturementioning

confidence: 99%

What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management

Shangguan

Wang

Sun

2020

IJERPH

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Since the first known case of a COVID-19 infected patient in Wuhan, China on 8 December 2019, COVID-19 has spread to more than 200 countries, causing a worldwide public health crisis. The existing literature fails to examine what caused this sudden outbreak from a crisis management perspective. This article attempts to fill this research gap through analysis of big data, officially released information and other social media sources to understand the root cause of the crisis as it relates to China's current management system and public health policy. The article draws the following conclusions: firstly, strict government control over information was the main reason for the early silencing of media announcements, which directly caused most people to be unprepared and unaware of COVID-19. Secondly, a choice between addressing a virus with an unknown magnitude and nature, and mitigating known public panic during a politically and culturally sensitive time, lead to falsehood and concealment. Thirdly, the weak autonomous management power of local public health management departments is not conducive for providing a timely response to the crisis. Finally, the privatization of many state-owned hospitals led to the unavailability of public health medical resources to serve affected patients in the Wuhan and Hubei Province. This article suggests that China should adopt a Singaporean-style public health crisis information management system to ensure information disclosure and information symmetry and should use it to monitor public health crises in real time. In addition, the central government should adopt the territorial administration model of a public health crisis and increase investment in public health in China.

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Section: Crisis Management Literaturementioning

confidence: 99%

What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management

Shangguan

Wang

Sun

2020

IJERPH

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“…Saint Germain et al (2007) worked on supply network coordination problem and discussed a multiagent coordination approach with factory control to manage the outbound and inbound logistics in multiple site/multiple organization topologies. To solve the Emergency Supply Chain (ESC) problem of supply of resources to the crisis-affected areas, Othman et al (2017) proposed the Decision Support System (DSS) based on multi-agent architecture and optimization tools. A dynamic pickup and delivery problem with dial-a-ride service system has been addressed by Núñez et al (2014) through a multi-objective model based predictive control method.…”

Section: Related Workmentioning

confidence: 99%

An MINLP model to support the movement and storage decisions of the Indian food grain supply chain

Mogale

Kumar

Tiwari

2018

Control Engineering Practice

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2018. An MINLP model to support the movement and storage decisions of the Indian food grain supply chain. Control Engineering Practice 70 , pp. Abstract:This paper addresses the novel three stage food grain distribution problem of Public Distribution System (PDS) in India which comprises of farmers, procurement centers, base silos and field silos. The Indian food grain supply chain consists of various activities such as procurement, storage, transportation and distribution of food grain. In order to curb transportation and storage losses of food grain, the Food Corporation of India (FCI) is moving towards the modernized bulk food grain supply chain system. This paper develops a Mixed Integer Non-Linear Programming (MINLP) model for planning the movement and storage of food grain from surplus states to deficit states considering the seasonal procurement, silo capacity, demand satisfaction and vehicle capacity constraints. The objective function of the model seeks to minimize the bulk food grain transportation, inventory holding, and operational cost. Therein, shipment cost contains the fixed and variable cost, inventory holding and operational cost considered at the procurement centers and base silos. The developed mathematical model is computationally complex in nature due to nonlinearity, the presence of numerous binary and integer variables along with a huge number of constraints, thus, it is very difficult to solve it using exact methods. Therefore, recently developed, Hybrid Particle-Chemical Reaction Optimization (HP-CRO) algorithm has been employed to solve the MINLP model. Different problem instances with growing complexities are solved using HP-CRO and the results are compared with basic Chemical Reaction Optimization (CRO) and Particle Swarm Optimization (PSO) algorithms. The results of computational experiments illustrate that the HP-CRO algorithm is competent enough to obtain the better quality solutions within reasonable computational time.

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“…Thereafter, Oliveira et al (2016) established a stochastic optimization model of origin-toterminal refineries to ensure the fundamental supply of crude oil. Based on two realistic military contingency events in Mali and Japan, Othman et al (2017) presented a multi-agent management system of petroleum emergency supply to realize the effective coordination of emergency transportation. It was widely believed that the technical innovations of petroleum emergency management could alleviate petroleum shortages.…”

Section: Petroleum Emergency Managementmentioning

confidence: 99%

Cross-regional emergency scheduling planning for petroleum based on the supernetwork model

Nie

Gao

2018

Pet. Sci.

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Petroleum, the most important energy source in the world, plays an essential role in securing economic development. If a petroleum shortage happens, it will severely disrupt production and life. Cross-regional emergency scheduling can effectively alleviate a petroleum shortage and further enhance the efficiency of the emergency response. Considering the general lack of focus on cross-regional petroleum dispatching management, we propose a three-layer emergency scheduling network for petroleum based on a supernetwork model that can increase the regional emergency correlation by adding a transfer management process. Then, we compare the total demand for petroleum and the emergency costs considered in the petroleum emergency scheduling supernetwork model (the single-region and the cross-region scenarios). The result shows that the cross-regional emergency scheduling pattern can effectively enhance the efficiency of the emergency preparations and reduce the emergency costs in most cases. However, when the vulnerabilities in the crossregional link grow or the regional linkage decreases, the effect of single-regional scheduling is better. In addition, the advantages of the cross-regional emergency scheduling network will be strengthened with an increase in its maximum emergency capability. Nonetheless, this advantage will disappear when the petroleum demand in the crisis layer reaches the maximum emergency response capacity. Finally, according to the comparative analysis simulation among scenarios, certain strategic policy recommendations are suggested to improve the petroleum emergency scheduling ability in regions. These recommendations include strengthening the cross-regional coordination mechanism, increasing the modes of petroleum transportation and enhancing the carrying capacity of regional emergency routes.

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An agent-based Decision Support System for resources' scheduling in Emergency Supply Chains

Cited by 49 publications

References 32 publications

What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management

What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management

An MINLP model to support the movement and storage decisions of the Indian food grain supply chain

Cross-regional emergency scheduling planning for petroleum based on the supernetwork model

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