Emergency Scheduling Research Articles

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

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 cross-regional 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.

Disaster Rescue Task Scheduling: An Evolutionary Multiobjective Optimization Approach

Efficient rescue task scheduling plays a key role in disaster rescue operations. In real-world applications, such an emergency scheduling problem often involves multiple objectives, complex constraints, inherent uncertainty, and limited response time requirement. In this paper, we propose a fuzzy multiobjective optimization problem of rescue task scheduling, the aim of which is to simultaneously maximize the task scheduling efficiency and minimize the operation risk for the rescue team. We then develop an efficient multiobjective biogeography-based optimization (EMOBBO) algorithm for solving the problem. To cope with the uncertainty, we employ three correlated fuzzy ranking criteria, and use the concept of fuzzy dominance for comparing the dominance relation of solutions. In EMOBBO, we define new migration and mutation operators for effectively evolving the permutation-based solutions, use a problem-specific solution rearrangement mechanism for filtering out inefficient solutions, and employ a local neighborhood structure to suppress premature convergence. Computational experiments show that the proposed EMOBBO algorithm outperforms some state-of-the-art evolutionary multiobjective optimization algorithms, and our algorithm has been successfully applied to several real-world disaster rescue operations in recent years.

Flood and Waterlogging Disaster Management System in Shenzhen River Basin

In recent years, "see the sea" in the rainy season has become a high frequency event in cities. Urban flood and waterlogging which are increasing day by day has influenced residents' lives seriously especially in large cities with high population aggregation. As a coastal city with low altitude, Shenzhen, where has a high requirement for the urban drainage system, not only has to face abundant in rainfall but also has to cope with the tide. In this paper, the disaster reduction systems such as rainwater collection, drainage system, flood storage and detention basin, reservoirs and pumping station in the Shenzhen River basin are analyzed and the operation effect is studied. In general, the flood management system of overall planning, emergency scheduling, preparation before flood, key area on duty, and post-rain response has achieved a high level and played an active role in disaster prevention and reduction. The conclusions that Shenzhen River basin has a complete and efficient system of urban flood and waterlogging management, the rainwater collecting and discharging system can meet the requirement of the city and modern design concepts of blocking, storaging, draining, pumping, scheduling which have effectively reduced the disaster have been come.

A Local-Optimization Emergency Scheduling Scheme With Self-Recovery for a Smart Grid

With the widespread applications of Internet of Things (IoT), the emergency response performance for large-scale network packets is facing serious challenge, especially for renewable distributed energy resources monitoring in a smart grid. Therefore, how to improve the real-time performance of the emergency data packets has been a critical issue. Traditional packet scheduling schemes and topology optimization strategies are not suitable for a large-scale IoT-based smart grid. To address this problem, this paper proposes a new packet scheduling scheme named LOES, which first combines the priority-based packet scheduling scheme with local optimization. We exchange local geographic information to reduce the hop counts and distance between distributed source nodes and sink nodes. Each destination node determines the packet scheduling sequence according to the received emergency information. Finally, we compare LOES with first come first serve, multilevel scheme, and dynamic multilevel priority packet scheduling scheme using packet loss rate, packet waiting time, and average packet end-to-end delay as metrics. The simulation results show that LOES outperforms these previous scheduling schemes.

Mission planning optimization of video satellite for ground multi-object staring imaging

This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

Programming model of emergency scheduling with combined air–ground transportation

With the effects of dynamic, multi-source, and uncertain features of disaster situations and information on the demand of supplies taken into consideration, this article establishes a scheduling model of a dynamic road network under road network damage conditions according to the min–max principle to make the entire ground scheduling process resemble an actual rescue scene. A scheduling model with collaborative air–ground transportation is proposed with the transport time, transportation cost, and utilization rate of the rescue aircraft taken into account. Results indicate that the model is feasible and effective under different damage degrees of road networks. An analysis of a comparative example among air transportation, road transportation, and combined air–ground transportation, shows that the combined air–ground transportation scheduling model could improve transportation efficiency and guarantee the timeliness and accuracy of rescue scheduling.

Bi-Objective Scheduling of Fire Engines for Fighting Forest Fires: New Optimization Approaches

It is challenging to perform emergency scheduling for fighting forest fires subject to limited rescue resources (i.e., vehicles with fire engines), since extinguishing each fire point should take into account multiple factors, such as the actual fire spreading speed, distance from fire engine depot to fire points, fire-fighting speed of fire engines, and the number of dispatched vehicles. This paper investigates a bi-objective rescue vehicle scheduling problem for multi-point forest fires, which aims to optimally dispatch a limited number of fire engines to extinguish fires. The objectives are to minimize the total fire-extinguishing time and the number of dispatched fire engines. For this problem, we first develop an integer program that is an improved and simplified version of an existing one. After exploring some properties of the problem, we develop an exact dynamic programming algorithm and a fast greedy heuristic method. Computational results for a real-life instance, and benchmark and large-size randomly generated instances confirm the effectiveness and efficiency of the proposed model and algorithms. Besides, a bi-objective integer program is developed to address the multi-depot fire engine scheduling issue.

Pupal emergence pattern in cactophilic Drosophila and the effect of host plants.

Drosophila buzzatii and D. koepferae are sibling cactophilic species. The former breeds primarily on prickly pears (genus Opuntia) whereas the latter breeds on columnar cacti of the genera Cereus and Trichocereus, although with certain degree of niche overlapping. We examined the interspecific differences in diurnal temporal patterns of adult emergence from puparia and evaluated whether this behavior is affected by rearing in the different cactus hosts available in nature. We detected important host-dependent genetic variation for this trait differentially affecting the emergence schedule of these species. Diurnal pattern of emergence time was directly correlated with developmental time and negatively correlated with adult wing size, suggesting that early emergences are at least indirectly correlated with increased fitness. We discussed our results in terms of their putative effects on fitness and the genetic-metabolic pathways that would be presumably affected by host's nutritional-chemical differences.

Dual-Objective Scheduling of Rescue Vehicles to Distinguish Forest Fires via Differential Evolution and Particle Swarm Optimization Combined Algorithm

It is complex and difficult to perform the emergency scheduling of forest fires in order to reduce the operational cost and improve the efficiency of extinguishing fire services. A new research issue arises when: 1) decision-makers want to minimize the number of rescue vehicles (or fire-fighting ones) while minimizing the extinguishing time; and 2) decision-makers prefer to complete this task given limited vehicle resources. To do so, this paper presents a novel multiobjective scheduling model to handle forest fires subject to limited rescue vehicle (fire engine) constraints, in which a fire-spread speed model is introduced into this problem to better describe practical forestry fire. Moreover, a Multiobjective Hybrid Differential-Evolution Particle-Swarm-Optimization (MHDP) algorithm is proposed to create a set of Pareto solutions for this problem. This approach is applied to a real-world emergency scheduling problem of the forest fire in Mt. Daxing'anling, China. Its effectiveness is verified by comparing it with a genetic algorithm and particle swarm optimization algorithm. Experimental results show that the proposed approach is able to quickly produce satisfactory Pareto solutions.

Emergency scheduling for forest fires subject to limited rescue team resources and priority disaster areas

To enable immediate and efficient emergency scheduling during forest fires, we propose a novel emergency scheduling model for such fires subject to priority disaster areas and limited rescue team resources to minimize the total travel distance for rescue teams. Moreover, a hybrid intelligent algorithm integrating genetic algorithm (GA) and particle swarm optimization (PSO) is adopted to solve the proposed model. A case study is presented to illustrate the proposed model and the effectiveness of the proposed algorithm. The goal of this work is to analyze the emergency scheduling problem of forest fires subject to limited rescue teams and priority disaster areas. Both theoretical and simulation results demonstrate that the proposed model can perform effectively the quantitative analysis of an emergency involving forest fires. Such results can help decision makers to make better judgment when dealing with an emergency involving fires. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

AUTOMATED FORMOSAT IMAGE PROCESSING SYSTEM FOR RAPID RESPONSE TO INTERNATIONAL DISASTERS

FORMOSAT-2, Taiwan’s first remote sensing satellite, was successfully launched in May of 2004 into the Sun-synchronous orbit at 891 kilometers of altitude. With the daily revisit feature, the 2-m panchromatic, 8-m multi-spectral resolution images captured have been used for researches and operations in various societal benefit areas. This paper details the orchestration of various tasks conducted in different institutions in Taiwan in the efforts responding to international disasters. The institutes involved including its space agency-National Space Organization (NSPO), Center for Satellite Remote Sensing Research of National Central University, GIS Center of Feng-Chia University, and the National Center for High-performance Computing. Since each institution has its own mandate, the coordinated tasks ranged from receiving emergency observation requests, scheduling and tasking of satellite operation, downlink to ground stations, images processing including data injection, ortho-rectification, to delivery of image products. With the lessons learned from working with international partners, the FORMOSAT Image Processing System has been extensively automated and streamlined with a goal to shorten the time between request and delivery in an efficient manner. The integrated team has developed an Application Interface to its system platform that provides functions of search in archive catalogue, request of data services, mission planning, inquiry of services status, and image download. This automated system enables timely image acquisition and substantially increases the value of data product. Example outcome of these efforts in recent response to support Sentinel Asia in Nepal Earthquake is demonstrated herein.

Research on Cross-Regional Emergency Scheduling and Allocating Strategies

Aiming at the present situation of lacking of scientific and reasonable schemes in farm machinery emergency scheduling and allocating, farm machinery emergency scheduling and allocating mode leading by management department is proposed and the optimization model with the goal of cost as low as possible and completing emergency tasks within the prescribed period is established in the paper. According to the characteristics of farm machinery emergency scheduling and allocating, the scheduling and allocating algorithm with priority rules and the scheduling and allocating algorithm based on the non-cooperative game theory are proposed. Compared with two algorithms, the scheduling cost and the allocating amounts calculated by the algorithm based on the non-cooperative game theory are less than that of the algorithm with priority rules. It is concluded that the scheduling and allocating algorithm based on the non-cooperative game theory in the paper is more effective and reasonable.

A race against time: habitat alteration by snow geese prunes the seasonal sequence of mosquito emergence in a subarctic brackish landscape

Species compositions in highly seasonal habitats often exhibit predictable patterns through time. However, the roles that ecological interactions play in shaping the sequence of species phenologies through a season are largely unexplored. Across the tundra on the Hudson Bay Lowlands, extensive foraging by lesser snow goose populations has been driving alterations to the landscape. Here, I show that this widespread and dramatic disturbance increases evaporation rates of ephemeral ponds and consequently constricts the temporal availability of seasonal aquatic habitats for larval mosquitoes. I also show that this constriction decreases the temporal diversity of closely related univoltine mosquito species that have varying emergence schedules. Three species of mosquitoes emerged through the season from four sampled ephemeral ponds associated with no goose grubbing; only one species emerged, early in the season, from the four ponds that experienced heavy grubbing. This study demonstrates a mechanism for temporal composition change in a ubiquitous and abundant group of arthropods on the tundra. It does not show life history evolution of emergence time of mosquitoes; however, it highlights the rather unexplored role of ecological interactions in altering the diversity of phenologies across seasonal time.

Keep calm in a crisis: Best practices for emergency scheduling

ANAHEIM, CALIF. — In the winter of 2013, Oregon State University experienced a major snowstorm at the beginning of finals week, closing campus for two days. A total of 700 finals had to be rescheduled; five days of finals had to be compressed into three, and 18,000 students were impacted directly by the rescheduling. The Registrar's Office was given 48 hours to reschedule all finals, a process that usually takes more than two weeks.

The Distribution of Periodical Cicada (Hemiptera: Cicadidae:Magicicada) Brood II in 2013: Disjunct Emergences Suggest Complex Brood Origins

The periodical cicadas ( Magicicada spp.) of eastern North America are subdivided into “broods” or locally synchronized populations that share a common emergence schedule. Twelve extant broods have 17-year life cycles and three have 13-year cycles. Most broods contain three morphologically distinct species. In the late 19th century, Charles Marlatt (1898) published a groundbreaking series of maps and emergence schedules accompanied by a sequential numbering scheme designating the 17-year brood that emerged in 1893 “Brood I” (with other potential 17-year broods numbered up to XVII), and the 13-year brood that emerged in 1894 as “Brood XIX” (with potential broods up to XXX). Later editions of Marlatt's work (1907, 1923) added more distributional records. Marlatt's …

A decision support system for water supply emergency management with multiple sources

The construction of water transfer projects brings new challenges to water resources management, especially in water supply security with the use of multiple water sources. However, the operations of water diversion and water supply have been considered in separation in practice. In particular, there are few decision support systems (DSS) designed to tackle the challenges in emergency planning of water transfer operation. This paper describes a generic DSS which is designed for the operation of multiple water sources supply and complex water supply targets. Emergency management is incorporated in the DSS to provide more effective water supply under extreme conditions. Specifically, the emergency scheduling plans regenerate the water supply strategy of Biliuhe Reservoir and Yingnahe Reservoir, and then reduce the impact of severe drought year on Dalian. The scheduling results of the case study reveal that this DSS makes good use of mutual compensation functions among multiple water sources when it is applied to the water supply emergency management of Dalian in severe drought year. The results indicate this developed DSS can be easily generalized and further applied to similar cities in China and other countries in the world.

Research on the Resource Scheduling in Emergency Response Based on ACA

This paper mainly studies the emergency resource scheduling algorithms and optimization problems. Through study the effect of explain emergency supplies of resources system, understanding the characteristics of emergency resource, emergency scheduling characteristics and process, and the characteristics of the demand for resources. Emergency resource scheduling model for emergencies, and emergency management by learning the theory and method of study, effective analysis of disaster impact on resource supply system. Select the appropriate scheduling, to the disaster area resources required for effective and reasonable to rise and scheduling is advantageous to the resource scheduling work smoothly. Emergency resource scheduling model is established, provide certain theoretical support for the actual emergency scheduling decisions.

The Distribution of Periodical Cicada (Magicicada) Brood I in 2012 with Previously Unreported Disjunct Populations (Hemiptera: Cicadidae,Magicicada)

The spectacular periodical cicada ( Magicicada spp.) emergences of Eastern North America have long attracted attention (Kritsky 2004). While any given location sees an emergence just once every 13 or 17 years, different regions emerge on different schedules, so that periodical cicadas are divided into “broods,” or locally synchronized emergences on a common schedule. The broods appear to be mostly parapatric (non-overlapping) and they vary in size from regional to extremely localized (Marlatt 1923, Simon 1988); however, the biological significance of the broods is poorly understood. Much of our understanding of periodical cicada broods comes from a series of groundbreaking maps created in the late nineteenth century by Charles Marlatt (1923), who summarized knowledge of periodical cicada brood ranges and emergence schedules, updating the earlier work of C. V. Riley (1885). Marlatt's maps are still in use today, though time has revealed some of their weaknesses (Cooley et al. 2013a), including their tendency to overestimate some brood ranges (Marshall 2001). Periodical cicada Brood I is interesting precisely because earlier maps appear to overestimate or misplace its range. One colloquial name for this brood (the “Blue Ridge Brood”) appears inaccurate, as Marlatt's maps place Brood I in the Shenandoah Valley, or even on Allegheny Mountain and its foothills, rather than in the Blue Ridge Mountains (Fig. 1). Marlatt's map of Brood I also includes extensions into North Carolina, records east of the mountains along the seaboard, and records westward into the Ohio Valley and beyond. Possibly, these records may reflect confusion due to off-schedule emergences (“stragglers”) …

Male emergence schedule and dispersal behaviour are modified by mate availability in heterogeneous landscapes: evidence from the orange-tip butterfly.

Protandry (prior emergence of males) in insect populations is usually considered to be the result of natural selection acting directly on eclosion timing. When females are monandrous (mate once), males in high density populations benefit from early emergence in the intense scramble competition for mates. In low density populations, however, scramble competition is reduced or absent, and theoretical models predict that protandry will be less favoured. This raises the question of how males behave in heterogeneous landscapes characterized by high density core populations in a low density continuum. We hypothesized that disadvantaged late emerging males in a core population would disperse to the continuum to find mates. We tested this idea using the protandrous, monandrous, pierid butterfly Anthocharis cardamines (the orange-tip) in a core population in Cheshire, northwest England. Over a six-year period, predicted male fitness (the number of matings a male can expect during his residence time, determined by the daily ratio of virgin females to competing males) consistently declined to <1 in late season. This decline affected a large proportion (∼44%) of males in the population and was strongly associated with decreased male recapture-rates, which we attribute to dispersal to the surrounding continuum. In contrast, reanalysis of mark-release-recapture data from an isolated population in Durham, northeast England, showed that in the absence of a continuum very few males (∼3%) emerged when fitness declined to <1 in late season. Hence the existence of a low density continuum may lead to the evolution of plastic dispersal behaviour in high density core populations, maintaining late emerging males which would otherwise be eliminated by selection. This has important theoretical consequences, since a truncated male emergence curve is a key prediction in game theoretic models of emergence timing which has so far received limited support. Our results have implications for conservation, since plastic dispersal behaviour in response to imperfect emergence timing in core (source) populations could help to maintain sink populations in heterogeneous landscapes which would otherwise be driven to extinction by low mate encounter-rates (Allee effects).

Emergency scheduling of engineering rescue tasks in disaster relief operations and its application in China

AbstractDisaster relief operations typically involve a large number of engineering rescue tasks, the efficient completion of which is vital to the success of the operations. The paper establishes a model of emergency scheduling of engineering rescue tasks in disaster relief operations, which involves multiple rescue teams and tasks, different and, perhaps fuzzy, processing times, as well as different importance weights of the tasks. We then propose a method based on biogeography‐based optimization, develop effective migration and mutation operators, and employ a multiobjective optimization approach for providing a set of candidate solutions for decision support. Computational experiments demonstrate that our approach exhibits competitive performance on a set of test problems. The proposed model and method have been successfully applied to the recent 2013 Dingxi earthquake that occurred in China.