Vehicle Routing Problem (VRP) is a real life constraint satisfaction problem to find minimal travel distances of vehicles to serve customers. Capacitated VRP (CVRP) is the simplest form of VRP considering vehicle capacity constraint. Constructive and clustering are the two popular approaches to solve CVRP. A constructive approach creates routes and attempts to minimize the cost at the same time...

The Capacitated Clustering Problem (CCP) consists of forming a specified number of clusters or groups from a set of elements in such a way that the sum of the weights of the elements in each cluster is within some capacity limits, and the sum of the benefits between the pairs of elements in the same cluster is maximized. This problem— which has been recently tackled with a GRASP/VNS approach— a...

this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

Clustering addresses the problem of assigning similar objects to groups. Since size clusters is often constrained in practical clustering applications, various capacitated problems have received increasing attention. We consider here p-median (CPMP) which p are selected as cluster centers (medians) such that total distance from these medians their assigned minimized. Each object associated with...

...................................................................................iii LIST OF FIGURES...........................................................................................iv INTRODUCTION..............................................................................................1 Scope and Motivation................................................................1 Basic D...

Affinity propagation (AP) was recently introduced as an unsupervised learning algorithm for exemplar-based clustering. We present a derivation of AP that is much simpler than the original one and is based on a quite different graphical model. The new model allows easy derivations of message updates for extensions and modifications of the standard AP algorithm. We demonstrate this by adjusting t...