Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...

Model checking is an automatic technique for software verification through which all reachable states are generated from an initial state to finding errors and desirable patterns. In the model checking approach, the behavior and structure of system should be modeled. Graph transformation system is a graphical formal modeling language to specify and model the system. However, modeling of large s...

Here, a mixed-integer linear programming model is developed to represent transportation system of students traveling from/to university campus. The concept ridesharing used and the mechanism combinatorial auctions incorporated within routing-based model. mathematical based on vehicle routing problem along with appropriate constraints accommodating features that express auction clearing phase. A...

This article introduces POPMUSIC a meta heuristic that has been successfully applied to various combinatorial optimization problems This meta heuristic is especially useful for designing heuristic methods for large combinatorial problems that can be partially optimized The basic idea is to optimize sub parts of solutions until a local optimum is reached Implementations of the technique to large...

Flood is a common global natural hazard, and detailed flood susceptibility maps for specific watersheds are important management measures. We compute the map Kaiser watershed in Iran using machine learning models such as support vector (SVM), Particle swarm optimization (PSO), genetic algorithm (GA) along with ensembles (PSO-GA SVM-GA). The application of assessment mapping analyzed, future res...

This paper browses through some well-known meta-heuristic search strategies, and briefly discusses some of their recent applications to the VLSI layout design process. It starts with very brief description of the different phases of VLSI layout design, and a brief overview of Meta-Heuristic search strategies. Since most of the VLSI layout design problems are hard optimization problems, the conc...

Large-scale unconditional and conditional vertex p-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with p ...