nowadays, different methods are used to solve optimization problems which ,one of the newest is bco method that are inspired by the nature and derived from the social life of bees of these methods can be noted that bco is derived from the social life of bees. we use in this paper fuzzy logic for bee‟s decision stage. at the end, we solve two different problem that have already been solved by es...

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 ...

In recent years, meta-heuristics have become increasingly interesting in solving combinatorial problems including hardware-software partitioning. In this paper, we present a comparative study between some algorithms which involve meta-heuristics based on Tabu search, genetic algorithm and Binary Search Trees to address the problem of hardware-software partitioning. In fact, meta-heuristics can ...

Meta-heuristics have already received considerable attention in various engineering optimization fields. As one of the most rewarding tasks, eigenvalue optimization of truss structures is concerned in this study. In the proposed problem formulation the fundamental eigenvalue is to be maximized for a constant structural weight. The optimum is searched using Particle Swarm Optimization, PSO and i...

Meta-heuristics are algorithms which are applied to solve problems when conventional algorithms can not find good solutions in reasonable time; evolutionary algorithms are perhaps the most well-known examples of meta-heuristics. As there are many possible meta-heuristics, finding the most suitable meta-heuristic for a given problem is not a trivial task. In order to make this choice, one can de...

This paper models and solves the scheduling problem of cable manufacturing industries that minimizes total production cost, including processing, setup, storing costs. Two hybrid meta-heuristics, which combine simulated annealing variable neighbourhood search algorithms with tabu algorithm, are proposed. Applying some case-based theorems rules, a special initial solution optimal setup cost is o...

[1] corresponding author e-mail: [email protected]   [1] corresponding author e-mail: [email protected]   lot-sizing problems (lsps) belong to the class of production planning problems in which the availability quantities of the production plan are always considered as a decision variable. this paper aims at developing a new mathematical model for the multi-level capacitated lsp w...

This paper proposes a novel hybrid t-way test generation strategy (where t indicates interaction strength), called High Level Hyper-Heuristic (HHH). HHH adopts Tabu Search as its high level meta-heuristic and leverages on the strength of four low level meta-heuristics, comprising of Teaching Learning based Optimization, Global Neighborhood Algorithm, Particle Swarm Optimization, and Cuckoo Sear...

In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuris...