This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-O...

Bilevel programming, a tool for modeling decentralized decision problems, consists of the objective of the leader at its first level and that of the follower at the second level. Bilevel programming has been proved to be an Np-hard problem. Numerous algorithms have been developed for solving bilevel programming problems. These algorithms lack the required efficiency for solving a real problem. ...

this research, for the first time presents the flexible flow shop model of scheduling method for considering runway assignment and operations planning together. one of the advantages of the developed model is considering the procedures of air routes in terminal airspace and separation between consecutive aircraft which is very similar to the real world condition. there are different objective f...

In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...

this paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. first, the problem is formulated as a mixed integer linear programming model. then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. two experiments are carried out to evaluate th...

In this paper we are concerned with finding the Pareto optimal front or a good approximation to it. Since non-dominated solutions represent the goal in multiobjective optimisation, the dominance relation is frequently used to establish preference between solutions during the search. Recently, relaxed forms of the dominance relation have been proposed in the literature for improving the performa...

We combine concepts from numerous papers to provide a derivation and description of a generalized Probabilistic Multi-Hypothesis Tracker that can track multiple targets in a cluttered environment, utilizing multiple sensors and feature measurements, if available. Additionally, we provide a full derivation of the algorithm, including parts omitted or abbreviated in other work. We also provide an...

Article history: Received: 13.2.2015. Received in revised form: 24.3.2015. Accepted: 27.3.2015. In structural design optimization method, numerical techniques are increasingly used. In typical structural optimization problems there may be many locally minimum configurations. For that reason, the application of a global method, which may escape from the locally minimum points, remains essential....

This paper presents a parallel simulated annealing algorithm for solving the problem of mapping irregular parallel programs onto homogeneous processor arrays with regular topology. The algorithm constructs and uses joint transformations. These transformations guarantee a high degree of parallelism that is bounded below by d jNpj deg(Gp)+1 e, where jN p j is the number of task nodes in the mappe...

this study is devoted to the formulation of the network design problem of one-way streets and the application of simulated annealing (sa) algorithm to solve this problem for a large real network. it discusses some points of views on one-way street networks, the objective function used for design, the way in which design constraints may be considered, and the traffic problems concerning one-way ...