scholarly journals Dynamic Relay Satellite Scheduling Based on ABC-TOPSIS Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Shufeng Zhuang ◽  
Zhendong Yin ◽  
Zhilu Wu ◽  
Xiaoguang Chen
Keyword(s):  
Artificial Bee Colony ◽  
Dynamic Scheduling ◽  
Research Field ◽  
Scheduling Problem ◽  
Ideal Solution ◽  
Bee Colony ◽  
Order Preference ◽  
Simulation Results ◽  
Satellite Scheduling ◽  
Selection Of

Tracking and Data Relay Satellite System (TDRSS) is a space-based telemetry, tracking, and command system, which represents a research field of the international communication. The issue of the dynamic relay satellite scheduling, which focuses on assigning time resource to user tasks, has been an important concern in the TDRSS system. In this paper, the focus of study is on the dynamic relay satellite scheduling, whose detailed process consists of two steps: the initial relay satellite scheduling and the selection of dynamic scheduling schemes. To solve the dynamic scheduling problem, a new scheduling algorithm ABC-TOPSIS is proposed, which combines artificial bee colony (ABC) and technique for order preference by similarity to ideal solution (TOPSIS). The artificial bee colony algorithm is performed to solve the initial relay satellite scheduling. In addition, the technique for order preference by similarity to ideal solution is adopted for the selection of dynamic scheduling schemes. Plenty of simulation results are presented. The simulation results demonstrate that the proposed method provides better performance in solving the dynamic relay satellite scheduling problem in the TDRSS system.

scholarly journals Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorithm

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3059 ◽  
Author(s):  
Zhen Li ◽  
Yun Li ◽  
Yanbin Li
Keyword(s):  
Support Vector Machine ◽  
Performance Evaluation ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Energy Transition ◽  
Indicator System ◽  
Support Vector ◽  
Ideal Solution ◽  
Bee Colony ◽  
Order Preference

Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores the application of the support vector machine improved by the artificial bee colony algorithm (IABC-SVM) method in the energy transition performance evaluation process. It provides an intelligent evaluation tool for the evaluation of the regional energy transition performance. Firstly, the evaluation indicator system of energy transition is constructed from five dimensions: energy supply, demand, efficiency, institution, and environment. Then, the technique for order preference by a similar to ideal solution improved by a combination weighting (CW-TOPSIS) method and IABC-SVM are constructed. After that, according to the evaluation values of 30 provinces in China calculated by CW-TOPSIS, 10-fold cross validation is used to compare the errors of support vector machine (SVM), support vector machine optimized by the artificial bee colony algorithm (ABC-SVM), and IABC-SVM, which proves the effectiveness and accuracy of IABC-SVM in evaluating the performance of energy transition. Finally, the IABC-SVM is used to evaluate the energy transition performance of 30 provinces in 2016. Through a comparative analysis, the relevant suggestions of energy transition are put forward.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

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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