clustering technique is one of the most important techniques of data mining and is the branch of multivariate statistical analysis and a method for grouping similar data in to same clusters. with the databases getting bigger, the researchers try to find efficient and effective clustering methods so that they can make fast and real decisions. thus, in this paper, we proposed an improved ant syst...

In this paper we propose several heuristic algorithms that, using MPLS capabilities, provide network operators with a control framework for the routing plane. In particular, a monitoring block collects real-time measurements, such as the link load, and feeds them to a centralized decision block which runs a routing optimization algorithm. The output of the optimization process is then conveyed ...

This research addresses the mixed-model assembly line (MMAL) by considering various constraints. In MMALs, several types of products which their similarity is so high are made on an assembly line. As a consequence, it is possible to assemble and make several types of products simultaneously without spending any additional time. The proposed multi-objective model considers the balancing and sequ...

The topic of test case prioritization has been researched extensively in the past decade. However, current researches carried out on test case prioritization are mainly concerned with independent test cases in a structural testing environment. In a specification-based testing environment, however, some test cases are inter-case dependent and must follow certain sequences of execution. The objec...

The 18th EURO Summer/Winter Institute (ESWI XVIII) took place during the spring 2000 in Switzerland. The topic of ESWI XVIII, ‘‘Meta-heuristics in Combinatorial Optimization’’, was selected due to its great current scientific interest: indeed, in recent years, several meta-heuristics have proved to be highly efficient for the solution of difficult combinatorial optimization problems. The Instit...

Task scheduling in fog computing is one of the areas where researchers are having challenges as demand grows for use internet things (IoT) to access cloud resources. Many resource and optimization algorithms were used by many computing; some single techniques while others combined schemes achieve dynamic computing, assessed based on deterministic meta-heuristic find out solution task problem bu...

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first o...

Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), etc., for solving emerge...

In order to conquer the premature convergence problem and lower the cost of computing of the basic Ant Colony Algorithm (ACA), we present an adaptive ant colony algorithm, named AACA, coupled with a Pareto Local Search (PLS) algorithm and apply to the Vehicle Routing Problem (VRP) and Capacitated VRP (CVRP). By using the information entropy, the algorithm adjusts the pheromone updating strategy...