Search Results - subject:"Simulated annealing algorithm"

Modeling and solution of maximal covering problem considering gradual coverage with variable radius over multi-periods

Eydi, Alireza; Mohebi, Javad - In: RAIRO 52 (2018) 4/5, pp. 1245-1260

Persistent link: https://www.econbiz.de/10011987291

Application of Neural Network With New Hybrid Algorithm in Volcanic Rocks Seismic Prediction

Liu, Yanchao; Yan, Limei; Xu, Jianjun - In: International Journal of Cognitive Informatics and … 12 (2018) 4, pp. 55-68

This article has studied the application design and implementation of neural network with new hybrid algorithm in volcanic rocks prediction. It is considered that the convergence rate of EBP algorithm is slow, and the local minimum value can be obtained by EBP algorithm, and the approximation of...

Persistent link: https://www.econbiz.de/10012043715

A New Model of Projection Pursuit Grade Evaluation Model Based on Simulated Annealing Ant Colony Optimization Algorithm

Zhaomei, Gai; Rentao, Liu; Qiuxiang, Jiang - In: International Journal of Cognitive Informatics and … 12 (2018) 4, pp. 69-80

Projection pursuit model (PP) is widely used in many fields, especially quality evaluation. One of the biggest shortages of PP was that the projection direction is strongly influenced by relevant parameters. In order to solve this problem, many experts and scholars introduced all kinds of...

Persistent link: https://www.econbiz.de/10012043716

Heuristics-based time-aware multi-criteria test case prioritisation technique

Maheswari, R. Uma; Mala, D. Jeya - In: International journal of information systems and change … 9 (2017) 4, pp. 315-333

Persistent link: https://www.econbiz.de/10011858364

Direct Solution of Fuzzy Project Crashing Problem with Fuzzy Decision Variables using Tabu Search and Simulated Annealing Algorithms

Göçken, Tolunay - In: International Journal of Fuzzy System Applications (IJFSA) 6 (2017) 1, pp. 17-35

Project management is a very important field employed for scheduling activities and monitoring the progress, in competitive and fluctuating environments. Project crashing analysis is concerned with shortening the project duration time by accelerating some of its activities at an additional cost....

Persistent link: https://www.econbiz.de/10012044820

Improved Methods for Production Manufacturing Processes in Environmentally Benign Manufacturing

Tan, Xian-Chun; Wang, Yan-Yan; Gu, Bai-He; Mu, Ze-Kun; … - In: Energies 4 (2011) 9, pp. 1391-1409

level, a decision-making model for new production processes based on the Genetic Simulated Annealing Algorithm (GSAA) is …

Persistent link: https://www.econbiz.de/10010668098

A classification approach based on the outranking model for multiple criteria ABC analysis

Liu, Jiapeng; Liao, Xiuwu; Zhao, Wenhong; Yang, Na - In: Omega : the international journal of management science 61 (2016), pp. 19-34

Persistent link: https://www.econbiz.de/10011475665

Planning and optimization of intermodal hub-and-spoke network under mixed uncertainty

Yang, Kai; Yang, Lixing; Gao, Ziyou - In: Transportation research / E : an international journal 95 (2016), pp. 248-266

Persistent link: https://www.econbiz.de/10011623793

Independent Component Analysis Via Copula Techniques

Chen, Ray-Bing; Guo, Meihui; Härdle, Wolfgang; Huang, … - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2008

matrix, Signal/noise ratio, Simulated annealing algorithm. 1 Introduction Independent component analysis (ICA) solves an …- sional case. Derivative-free optimization methods, such as genetic algorithm, simulated annealing algorithm, direct search … method and so on, can aid to solve this minimization problem. Herein, the simulated annealing algorithm, pro- posed by …

Persistent link: https://www.econbiz.de/10005677950

Independent component analysis via copula techniques

Chen, Ray-Bing; Guo, Meihui; Härdle, Wolfgang Karl; … - 2008

Independent component analysis (ICA) is a modern factor analysis tool developed in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then...

Persistent link: https://www.econbiz.de/10010274138