نتایج جستجو برای: supplier clustering problem and particle swarm optimization

تعداد نتایج: 17011094  

2009
Esmaeil Mehdizadeh Reza Tavakkoli-Moghaddam

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...

A mobile ad-hoc network (MANET), a set of wirelessly connected sensor nodes, is a dynamic system that executes hop-by-hop routing independently with no external help of any infrastructure. Proper selection of cluster heads can increase the life time of the Ad-hoc network by decreasing the energy consumption. Although different methods have been successfully proposed by researchers to tackle...

A mobile ad-hoc network (MANET), a set of wirelessly connected sensor nodes, is a dynamic system that executes hop-by-hop routing independently with no external help of any infrastructure. Proper selection of cluster heads can increase the life time of the Ad-hoc network by decreasing the energy consumption. Although different methods have been successfully proposed by researchers to tackle...

Journal: :مهندسی صنایع 0
عاطفه کهفی اردکانی کارشناسی ارشد مهندسی صنایع- دانشکده فنی و مهندسی- دانشگاه پیام¬نور تهران فرناز برزین پور استادیار دانشکده مهندسی صنایع- دانشگاه علم و صنعت ایران رضا توکلی¬مقدم استاد گروه مهندسی صنایع- دانشکده فنی و مهندسی- دانشگاه تهران

cellular manufacturing system is one of the most important applications of group technology. design of this system involves many structural and operational issues, in which the cell formation and production planning are two important steps. in this paper, a new mathematical model is proposed for integration of cell formation and production planning problems with the aim of minimizing the overal...

2015
K. Arun Prabha Karthi Keyani Visalakshi

Clustering in data mining is a discovery process that groups a set of data so as to maximize the intracluster similarity and to minimize the inter-cluster similarity. The K-Means algorithm is best suited for clustering large numeric data sets when at possess only numeric values. The K-Modes extends to the K-Means when the domain is categorical. But in some applications, data objects are describ...

Journal: :journal of chemical and petroleum engineering 2014
abdolnabi hashemi afshin ghanbarzadeh siamak hosseini

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی (نوشیروانی) بابل - دانشکده مهندسی برق و کامپیوتر 1393

مسئله ی یافتن کلیک بیشینه گراف maximum clique problem (mcp)، از جمله مسائل np-complete است که به یافتن بزرگترین زیرگراف کامل در یک گراف ساده اشاره دارد و در موارد متنوعی از جمله نظریه کدگذاری، هندسه و شبکه های اجتماعی کاربرد دارد. در این پژوهش الگوریتمی ترکیبی برای حل مسئله ی کلیک بیشینه گراف پیشنهاد شده است. این الگوریتم ترکیبی از یک روش حریصانه ابتکاری و الگوریتم های مبتنی بر هوش جمعی بهینه س...

Clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. The aim of clustering is to collect data points. In this paper, a Cultural Algorithm (CA) is presented to optimize partition with N objects into K clusters. The CA is one of the effective methods for searching into the problem space in order to find a n...

Journal: :journal of ai and data mining 2015
z. izakian m. mesgari

with rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. clustering analysis as the most commonly used function of data mining, has attracted many researchers in computer science. because o...

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

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