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...

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...

the set covering problem (scp) is a well-known combinatorial optimization problem. this paper investigates development of a local branching approach for the scp. this solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the mixed integer programming solver. the algorithm parameters are tuned by design of experiments approach. the proposed method is te...

In this paper we address a hybrid flow shop scheduling problem considering the minimization of the sum of the total earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, we propose an ant colony optimization method to deal with this problem. Our proposed method has s...

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...

Various meta-heuristic optimization approaches have been recently created and applied in different areas. Many of these approaches are inspired by swarm behaviors in the nature. This paper studies the solving optimization problems using Black Hole Algorithm (BHA) which is a population-based algorithm. Since the performance of this algorithm was not tested in mathematical functions, we have stud...