2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)最新文献

An extended bilevel programming model and its kth-best algorithm for dynamic decision making in emergency situations 紧急情况下动态决策的扩展双层规划模型及其第k优算法

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-12 DOI: 10.1109/MCDM.2014.7007194

Hong Zhou, Jie Lu, Guangquan Zhang

引用次数: 1

A bottom-up implementation of Path-Relinking for Phylogenetic reconstruction applied to Maximum Parsimony 一个自下而上的路径链接实现系统发育重建应用于最大简约

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007202

K. Ortiz, Jean-Michel Richer, D. Lesaint, E. Rodriguez-Tello

引用次数: 1

Multi-Genomic Algorithms Multi-Genomic算法

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007187

Mathias Ngo, R. Labayrade

引用次数: 1

Gene interaction networks boost genetic algorithm performance in biomarker discovery 基因相互作用网络提高遗传算法在生物标志物发现中的性能

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007200

Charalampos N. Moschopoulos, D. Popovic, R. Langone, J. Suykens, B. Moor, Y. Moreau

{"title":"Gene interaction networks boost genetic algorithm performance in biomarker discovery","authors":"Charalampos N. Moschopoulos, D. Popovic, R. Langone, J. Suykens, B. Moor, Y. Moreau","doi":"10.1109/MCDM.2014.7007200","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007200","url":null,"abstract":"In recent years, the advent of high-throughput techniques led to significant acceleration of biomarker discovery. In the same time, the popularity of machine learning methods grown in the field, mostly due to inherit analytical problems associated with the data resulting from these massively parallelized experiments. However, learning algorithms are very often utilized in their basic form, hence sometimes failing to consider interactions that are present between biological subjects (i.e. genes). In this context, we propose a new methodology, based on genetic algorithms, that integrates prior information through a novel genetic operator. In this particular application, we rely on a biological knowledge that is captured by the gene interaction networks. We demonstrate the advantageous performance of our method compared to a simple genetic algorithm by testing it on several microarray datasets containing samples of tissue from cancer patients. The obtained results suggest that inclusion of biological knowledge into genetic algorithm in the form of this operator can boost its effectiveness in the biomarker discovery problem.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117056752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interval linear optimization problems with fuzzy inequality constraints 模糊不等式约束下的区间线性优化问题

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007197

I. Alolyan

引用次数: 0

Partially Optimized Cyclic Shift Crossover for Multi-Objective Genetic Algorithms for the multi-objective Vehicle Routing Problem with time-windows 带时间窗的多目标车辆路径问题多目标遗传算法的部分优化循环移位交叉

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007195

Djamalladine Mahamat Pierre, M. N. Zakaria

{"title":"Partially Optimized Cyclic Shift Crossover for Multi-Objective Genetic Algorithms for the multi-objective Vehicle Routing Problem with time-windows","authors":"Djamalladine Mahamat Pierre, M. N. Zakaria","doi":"10.1109/MCDM.2014.7007195","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007195","url":null,"abstract":"The complexity of the Vehicle Routing Problems (VRPs) and their applications in our day to day life has garnered a lot of attentions in the area of optimization. Recently, attentions have turned to multi-objective VRPs with Multi-Objective Genetic Algorithms (MOGAs). MOGAs, thanks to its genetic operators such as selection, crossover, and/or mutation, constantly modify a population of solutions in order to find optimal solutions. However, given the complexity of VRPs, conventional crossover operators have major drawbacks. The Best Cost Route Crossover is lately gaining popularity in solving multi-objective VRPs. It employs a brute force approach to generate new children. Such approach may be unacceptable when presented with a relatively large problem instance. In this paper, we introduce a new crossover operator, called Partially Optimized Cyclic Shift Crossover (POCSX). A comparative study, between a MOGA based on POCSX, and a MOGA which is based on the Best Cost Route Crossover affirms the level of competitiveness of the former.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117106204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Clustering Decision Makers with respect to similarity of views 基于观点相似性的决策者聚类

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007186

Edward Abel, L. Mikhailov, J. Keane

引用次数: 6

A perceptual fuzzy neural model 一种感知模糊神经模型

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007188

J. T. Rickard, J. Aisbett

引用次数: 0

Multi-objective evolutionary approach for the satellite payload power optimization problem 卫星有效载荷功率优化问题的多目标进化方法

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007208

Emmanuel Kieffer, A. Stathakis, Grégoire Danoy, P. Bouvry, E. Talbi, G. Morelli

{"title":"Multi-objective evolutionary approach for the satellite payload power optimization problem","authors":"Emmanuel Kieffer, A. Stathakis, Grégoire Danoy, P. Bouvry, E. Talbi, G. Morelli","doi":"10.1109/MCDM.2014.7007208","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007208","url":null,"abstract":"Today's world is a vast network of global communications systems in which satellites provide high-performance and long distance communications. Satellites are able to forward signals after amplification to offer a high level of service to customers. These signals are composed of many different channel frequencies continuously carrying real-time data feeds. Nevertheless, the increasing demands of the market force satellite operators to develop efficient approaches to manage satellite configurations, in which power transmission is one crucial criterion. Not only the signal power sent to the satellite needs to be optimal to avoid large costs but also the power of the downlink signal has to be strong enough to ensure the quality of service. In this work, we tackle for the first time the bi-objective input/output power problem with multi-objective evolutionary algorithms to discover efficient solutions. A problem specific indirect encoding is proposed and the performance of three state-of-the-art multi-objective evolutionary algorithms, i.e. NSGA-II, SPEA2 and MOCell, is compared on real satellite payload instances.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127394083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Selection of solutions in multi-objective optimization: Decision making and robustness 多目标优化解的选择:决策与鲁棒性

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) Pub Date : 2014-12-01 DOI: 10.1109/MCDM.2014.7007183

A. Gaspar-Cunha, J. Ferreira, J. Covas, Gustavo Recio

引用次数: 5