ON-LINE NETWORK SCHEDULING IN EMERGENCY OPERATION FOR MEDICAL RESOURCES WITH SINGLE-PROCESSOR SINGLE-DESTINATION

Emergency Management has received more and more attention in the recent years. Most research in this eld focused on evacuation of victims from dangerous places to safe places, but little on allocation of medical resources to safe places and/or transportation tools to the dangerous places. This thesis studies the problem of delivering medical resources from medical centers to the temporary aid site in a disaster-a ected area to help the wounded victims. In particular, this thesis describes a new algorithm for solving this problem. As requirements of medical resources for a disaster a ected area are not known in advance, the problem is in the so-called on-line environment. The algorithm for such a problem is also called on-line algorithm. The evaluation criterion for such an on-line algorithm is the so-called competitive ratio. This thesis considers four cases of such a problem: (1) the capacity of vehicles for transporting medical resources and the number of vehicles are both in nite, (2) the capacity of vehicles is in nite but the number of vehicles is one, (3) the capacity of vehicles is nite and the number of vehicles is in nite, (4) the capacity of vehicles is nite and the number of vehicles is one. Algorithms for the four cases are called H1, H2, H3, and H4, ii respectively. For all these cases, this thesis presents properties, appropriate on-line algorithms and theoretical analysis of these algorithms. The result of the analysis shows that H1 and H3 are optimal based on the competitive ratio criterion while the other two have a very small gap in terms of the optimum criterion. The thesis also presents a case study for having a sense of the performance of H2 and demonstrating practicality of the developed algorithms. The result of this thesis has contributions to the eld of resource planning and scheduling and has application in not only emergency management but also supply chain management in manufacturing and construction

Evacuation by earliest arrival flows

Als Evakuierungsprobleme mittels dynamischer Flüsse werden in der Literatur unter Anderem das Quickest Transshipment Problem, das Earliest Arrival Transshipment Problem und das Earliest Arrival Maximalflussproblem betrachtet. In der vorliegenden Arbeit wird sowohl ein exakter polynomialer Algorithmus für das Earliest Arrival Transshipment Problem angegeben als auch das Earliest Arrival Maximalflussproblem für Netzwerke mit flussabhängigen Fahrzeiten untersucht. Dabei wird festgestellt, dass in solchen Netzwerken die Earliest Arrival Eigenschaft verletzt wird. Daher wird ein abgewandeltes Problem untersucht, bei dem die Verspätung minimiert wird. Im Bereich der Datenevakuierung ist zu beachten, dass die Kopierfähigkeit eines Datums die Problemstellung verändert. Für dieses Problem wurden Algorithmen für Datenflüsse auf Pfaden angegeben

Using a Public Safety Radio Network for Information Negotiation between the Three-Tiered Command and Control Structure

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Using a Public Safety Radio Network for Information Negotiation between the Three-Tiered Command and Control Structure

Multi-organizational emergency operations require effective information sharing. Existing information management tools supporting a common operational picture mainly convey factual information. However, a growing body of literature recognizes the importance of sharing interpretations and implications among the involved stakeholders for building a common situational understanding. This study aims to identify information that must be negotiated across the strategic, tactical, and operational command and control structures (C2S) for developing common situational understanding. Based on 33 interviews and a survey of emergency management stakeholders, information elements on the semantic and pragmatic levels are identified. Further, the results suggest how to use a secure radio network for facilitating information sharing so that the involved organizations can monitor and negotiate important information. These insights provide important lessons for improving information sharing in the emergency management domain

On finding paths and flows in multicriteria, stochastic and time-varying networks

This dissertation addresses two classes of network flow problems in networks with multiple, stochastic and time-varying attributes. The first problem class is concerned with providing routing instructions with the ability to make updated decisions as information about travel conditions is revealed for individual travelers in a transportation network. Three exact algorithms are presented for identifying all or a subset of the adaptive Pareto-optimal solutions with respect to the expected value of each criterion from each node to a desired destination for each departure time in the period of interest. The second problem class is concerned with problems of determining the optimal set of a priori path flows for evacuation in capacitated networks are addressed, where the time-dependent and stochastic nature of arc attributes and capacities inherent in these problems is explicitly considered. The concept of Safest Escape is formulated for developing egress instructions. An exact algorithm is proposed to determine the pattern of flow that maximizes the minimum path probability of successful arrival of supply at the sink. While the Safest Escape problem considers stochastic, time-varying capacities, arc travel times, while time-varying, are deterministic quantities. Explicit consideration of stochastic and time-varying travel times makes the SEscape problem and other related problems significantly more difficult. A meta-heuristic based on the principles of genetic algorithms is developed for determining optimal path flows with respect to several problems in dynamic networks, where arc traversal times and capacities are random variables with probability mass functions that vary with time. The proposed genetic algorithm is extended for use in more difficult, stochastic, time-varying and multicriteria, capacitated networks, for which no exact, efficient algorithms exist. Several objectives may be simultaneously considered in determining the optimal flow pattern: minimize total time, maximize expected flow and maximize the minimum path probability of successful arrival at the sink (the objective of the SEscape problem). Numerical experiments are conducted to assess the performance of all proposed approaches

Advances and Novel Approaches in Discrete Optimization

Discrete optimization is an important area of Applied Mathematics with a broad spectrum of applications in many fields. This book results from a Special Issue in the journal Mathematics entitled ‘Advances and Novel Approaches in Discrete Optimization’. It contains 17 articles covering a broad spectrum of subjects which have been selected from 43 submitted papers after a thorough refereeing process. Among other topics, it includes seven articles dealing with scheduling problems, e.g., online scheduling, batching, dual and inverse scheduling problems, or uncertain scheduling problems. Other subjects are graphs and applications, evacuation planning, the max-cut problem, capacitated lot-sizing, and packing algorithms

SUPPLY CHAIN SCHEDULING FOR MULTI-MACHINES AND MULTI-CUSTOMERS

Manufacturing today is no longer a single point of production activity but a chain of activities from the acquisition of raw materials to the delivery of products to customers. This chain is called supply chain. In this chain of activities, a generic pattern is: processing of goods (by manufacturers) and delivery of goods (to customers). This thesis concerns the scheduling operation for this generic supply chain. Two performance measures considered for evaluation of a particular schedule are: time and cost. Time refers to a span of the time that the manufacturer receives the request of goods from the customer to the time that the delivery tool (e.g. vehicle) is back to the manufacturer. Cost refers to the delivery cost only (as the production cost is considered as fi xed). A good schedule is thus with short time and low cost; yet the two may be in conflict. This thesis studies the algorithm for the supply chain scheduling problem to achieve a balanced short time and low cost. Three situations of the supply chain scheduling problem are considered in this thesis: (1) a single machine and multiple customers, (2) multiple machines and a single customer and (3) multiple machines and multiple customers. For each situation, di fferent vehicles characteristics and delivery patterns are considered. Properties of each problem are explored and algorithms are developed, analysed and tested (via simulation). Further, the robustness of the scheduling algorithms under uncertainty and the resilience of the scheduling algorithms under disruptions are also studied. At last a case study, about medical resources supply in an emergency situation, is conducted to illustrate how the developed algorithms can be applied to solve the practical problem. There are both technical merits and broader impacts with this thesis study. First, the problems studied are all new problems with the particular new attributes such as on-line, multiple-customers and multiple-machines, individual customer oriented, and limited capacity of delivery tools. Second, the notion of robustness and resilience to evaluate a scheduling algorithm are to the best of the author's knowledge new and may be open to a new avenue for the evaluation of any scheduling algorithm. In the domain of manufacturing and service provision in general, this thesis has provided an e ffective and effi cient tool for managing the operation of production and delivery in a situation where the demand is released without any prior knowledge (i.e., on-line demand). This situation appears in many manufacturing and service applications

Assessment Of Instructional Presentation For Emergency Evacuation Assistive Technology

It is often the case that emergency first responders are well equipped and trained to deal with a situation that involves evacuation of someone with a physical disability. However, emergency responders are not always the first line of defense, or they may be otherwise occupied with assisting others. This research examined the effects of instructions for emergency stair travel devices on untrained or novice users. It was hypothesized that through redesign of the evacuation instructions, untrained individuals would be able to successfully prepare an evacuation chair and secure someone with a disability more effectively and efficiently. A prepost study design was used with an instructional redesign occurring as the manipulation between phases. There was an improved subjective understanding and improved performance metrics, such as reduced time on task and a reduction of the number of instructional glances, across three evacuation chairs when using the redesigned instruction sets. The study demonstrated that visual instruction style can account for a significant portion of explained variance in the operation of emergency stair travel devices. It also showed that improvements in instruction style can reduce time on task across device type and age group. The study failed to demonstrate that there was a performance decrement for older adults in comparison to younger adults because of the cognitive slowing of older adult information processing abilities. Results from this study can be used to support future iterations of the Emergency Stair Travel Device Standard (RESNA ED-1) to ensure that instructional design is standardized and optimized for the best performance possible

An Introduction to Network Flows Over Time

Flow variation over time is an important feature in network flow problems arising in various applications such as road or air traffic control, production systems, communication networks (e.g., the Internet), and financial flows. In such applications, flow values on arcs are not constant but may change over time. Moreover, there is a second temporal dimension in these applications. Usually, flow does not travel instantaneously through a network but requires a certain amount of time to travel through each arc. In particular, when routing decisions are being made in one part of a network, the effects can be seen in other parts of the network only after a certain time delay. Not only the amount of flow to be transmitted but also the time needed for the transmission plays an essential role