scholarly journals MULTI-SATELLITE SCHEDULING APPROACH FOR DYNAMIC AREAL TASKS TRIGGERED BY EMERGENT DISASTERS

2016 ◽  
Vol XLI-B1 ◽  
pp. 475-481 ◽  
Author(s):  
X. N. Niu ◽  
X. J. Zhai ◽  
H. Tang ◽  
L. X. Wu
Keyword(s):  
Disaster Response ◽  
Optimal Solution ◽  
Dynamic Imaging ◽  
Target Area ◽  
Satellite Mission ◽  
Efficient Manner ◽  
Scheduling Model ◽  
Proposed Model ◽  
Disaster Situation ◽  
Satellite Scheduling

The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

scholarly journals MULTI-SATELLITE SCHEDULING APPROACH FOR DYNAMIC AREAL TASKS TRIGGERED BY EMERGENT DISASTERS

2016 ◽  
Vol XLI-B1 ◽  
pp. 475-481 ◽  
Author(s):  
X. N. Niu ◽  
X. J. Zhai ◽  
H. Tang ◽  
L. X. Wu
Keyword(s):  
Disaster Response ◽  
Optimal Solution ◽  
Dynamic Imaging ◽  
Target Area ◽  
Satellite Mission ◽  
Efficient Manner ◽  
Scheduling Model ◽  
Proposed Model ◽  
Disaster Situation ◽  
Satellite Scheduling

The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

scholarly journals MULTI-SATELLITE OBSERVATION SCHEDULING FOR LARGE AREA DISASTER EMERGENCY RESPONSE

2018 ◽  
Vol XLII-3 ◽  
pp. 1327-1331 ◽  
Author(s):  
X. N. Niu ◽  
H. Tang ◽  
L. X. Wu
Keyword(s):  
Disaster Response ◽  
Satellite Observation ◽  
Large Area ◽  
Efficient Manner ◽  
2008 Wenchuan Earthquake ◽  
Scheduling Model ◽  
Scheduling Method ◽  
Initial Imaging ◽  
Disaster Scenario ◽  
Satellite Scheduling

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

scholarly journals Robust Satellite Scheduling Approach for Dynamic Emergency Tasks

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Xuejun Zhai ◽  
Xiaonan Niu ◽  
Hong Tang ◽  
Lixin Wu ◽  
Yonglin Shen
Keyword(s):  
Genetic Algorithm ◽  
Heuristic Algorithm ◽  
Optimal Solution ◽  
Simulation Experiments ◽  
Multiobjective Genetic Algorithm ◽  
Scheduling Model ◽  
Rapid Responses ◽  
Earth Observation Satellites ◽  
Satellite Scheduling ◽  
Combined Algorithm

Earth observation satellites play a significant role in rapid responses to emergent events on the Earth’s surface, for example, earthquakes. In this paper, we propose a robust satellite scheduling model to address a sequence of emergency tasks, in which both the profit and robustness of the schedule are simultaneously maximized in each stage. Both the multiobjective genetic algorithm NSGA2 and rule-based heuristic algorithm are employed to obtain solutions of the model. NSGA2 is used to obtain a flexible and highly robust initial schedule. When every set of emergency tasks arrives, a combined algorithm called HA-NSGA2 is used to adjust the initial schedule. The heuristic algorithm (HA) is designed to insert these tasks dynamically to the waiting queue of the initial schedule. Then the multiobjective genetic algorithm NSGA2 is employed to find the optimal solution that has maximum revenue and robustness. Meanwhile, to improve the revenue and resource utilization, we adopt a compact task merging strategy considering the duration of task execution in the heuristic algorithm. Several experiments are used to evaluate the performance of HA-NSGA2. All simulation experiments show that the performance of HA-NSGA2 is significantly improved.

scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

scholarly journals Onsite Disaster Response System for an Inclusive Society and Social Safety Net by Types of Disabilities: Focusing on the Welfare Facilities for the Disabled in "D City"

2020 ◽  
Vol 20 (2) ◽  
pp. 61-70
Author(s):  
Jiyeon Myeong ◽  
Hongjik Kim
Keyword(s):  
Emergency Management ◽  
Disaster Response ◽  
Safety Net ◽  
Management Research ◽  
Social Safety Net ◽  
Response System ◽  
The Disabled ◽  
Disaster Situation ◽  
Physical Limitations ◽  
Inclusive Society

As the types of disaster diversity and the occurrence of disaster became more frequent, complex damage is also increasing. The nation is making various efforts, including creating an emergency management system and supporting crisis management research, to minimize damage to property, facilities and lives that are caused by disasters. However, the practical system for those who have a disadvantage in terms of disaster awareness and early evacuation due to their physical limitations is still insufficient. In this study, the vulnerability of people with disabilities when it comes to disaster safety was analyzed by visiting the living facilities tailored for each type of disability by examing each facility's disaster resonse manual and observing the facilities. In addition, through surveying and interviewing employees and users of facilities, we analyzed the recognition of evacuation. Finally, this study proposed strengthening related disaster response policies to establish an inclusive society and a social safety net by analyzing behavioral patterns for each type of disability in the initial disaster situation.

scholarly journals Robust Design of Relief Distribution Networks Considering Uncertainty

2021 ◽  
Vol 13 (16) ◽  
pp. 9281
Author(s):  
Moddassir Khan Nayeem ◽  
Gyu M. Lee
Keyword(s):  
Disaster Response ◽  
Transportation Cost ◽  
Distribution Networks ◽  
Vital Role ◽  
Decision Makers ◽  
Distribution Centers ◽  
Proposed Model ◽  
Relief Distribution ◽  
Secondary Disasters ◽  
Post Disaster

In the post-disaster response phase, an efficient relief distribution strategy plays a vital role in alleviating suffering in disaster-stricken areas, which sometimes becomes challenging in humanitarian logistics. Most governments pre-located the relief goods at the pre-determined warehouses against possible disasters. Those goods must be shipped to the relief distribution centers (RDCs) to be further distributed to the victims in impacted areas upon the disasters. Secondary disasters can occur due to the first disaster and can occur relatively close in time and location, resulting in more suffering and making the relief distribution activities more challenging. The needs of additional RDCs must be determined as well in response to the secondary disasters. A robust optimization model is proposed to hedge against uncertainties in RDCs’ capacity and relief demand. Its objective is to minimize the sum of transportation cost, additional RDC cost, and shortage of commodities. The computational results are given to demonstrate the effectiveness of the proposed model. The sensitivity analysis gives an insight to the decision-makers.

scholarly journals Timetable Design for Urban Rail Line with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Ting Zhu ◽  
Bao-Hua Mao ◽  
Lu Liu ◽  
Ming-Gao Li
Keyword(s):  
Solution Method ◽  
Operating Cost ◽  
Capacity Constraints ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line ◽  
First Come First Serve ◽  
Waiting Cost ◽  
Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

Artificial Bee Colony-Based Approach for Privacy Preservation of Medical Data

2021 ◽  
pp. 1203-1221
Author(s):  
Shivlal Mewada ◽  
Sita Sharan Gautam ◽  
Pradeep Sharma
Keyword(s):  
Privacy Preservation ◽  
Artificial Bee Colony ◽  
Model Simulation ◽  
Privacy Preserving ◽  
Global Network ◽  
Sensitive Information ◽  
Healthcare Applications ◽  
Efficient Manner ◽  
Bee Colony ◽  
Proposed Model

A large amount of data is generated through healthcare applications and medical equipment. This data is transferred from one piece of equipment to another and sometimes also communicated over a global network. Hence, security and privacy preserving are major concerns in the healthcare sector. It is seen that traditional anonymization algorithms are viable for sanitization process, but not for restoration task. In this work, artificial bee colony-based privacy preserving model is developed to address the aforementioned issues. In the proposed model, ABC-based algorithm is adopted to generate the optimal key for sanitization of sensitive information. The effectiveness of the proposed model is tested through restoration analysis. Furthermore, several popular attacks are also considered for evaluating the performance of the proposed privacy preserving model. Simulation results of the proposed model are compared with some popular existing privacy preserving models. It is observed that the proposed model is capable of preserving the sensitive information in an efficient manner.

scholarly journals Group Scheduling Problems with Time-Dependent and Position-Dependent DeJong’s Learning Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Sun ◽  
Lei Ning ◽  
Jia-zhen Huo
Keyword(s):  
Polynomial Time ◽  
Completion Time ◽  
Learning Effect ◽  
Time Dependent ◽  
Total Weighted Completion Time ◽  
Group Scheduling ◽  
Scheduling Problems ◽  
Scheduling Model ◽  
Proposed Model ◽  
Weighted Completion Time

In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJong’s learning effect. The objectives of scheduling problems are to minimize makespan, the total completion time, and the total weighted completion time, respectively. We show that the problems remain solvable in polynomial time under the proposed model.

scholarly journals Application of a Multi-Satellite Dynamic Mission Scheduling Model Based on Mission Priority in Emergency Response

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1430 ◽  
Author(s):  
Jintian Cui ◽  
Xin Zhang
Keyword(s):  
Dynamic Scheduling ◽  
Search Algorithm ◽  
Earth Observation ◽  
Impact Factors ◽  
Scheduling Problem ◽  
Model Based ◽  
Scheduling Model ◽  
Earth Observation Satellites ◽  
Scheduling Plan ◽  
Satellite Scheduling

Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem of Earth observation satellites under emergency conditions, a multi-satellite dynamic mission scheduling model based on mission priority is proposed in this paper. A calculation model of mission priority is designed for emergency missions based on seven impact factors. In the satellite mission scheduling, the resource constraints of scheduling are analyzed in detail, and the optimization objective function is built to maximize the observation mission priority and mission revenues, and minimize the waiting time for missions that require urgency for execution time. Then, the hybrid genetic tabu search algorithm is used to obtain the initial satellite scheduling plan. In case of the dynamic arrival of new emergency missions before scheduling plan releases, a dynamic scheduling algorithm based on mission priority is proposed to solve the scheduling problem caused by newly arrived missions and to obtain the scheduling plan of newly arrived missions. A simulation experiment was conducted for different numbers of initial missions and newly arrived missions, and the scheduling results were evaluated with a model performance evaluation function. The results show that the execution probability of high-priority missions increased because the mission priority was taken into account in the model. In the case of more satellite resources, when new missions dynamically arrived, the satellite resources can be reasonably allocated to these missions based on the mission priority. Overall, this approach reduces the complexity of the dynamic adjustment and maintains the stability of the initial scheduling plan.

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