We describe a hybrid meta-heuristic algorithm for combinatorial optimization problems with a specific reference to the travelling salesman problem (TSP). The method is a combination of a genetic algorithm (GA) and greedy randomized adaptive search procedure (GRASP). A new adaptive fuzzy a greedy search operator is developed for this hybrid method. Computational experiments using a wide range of...

The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of thi...

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...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and pa...

Optimization of machining parameters is a vital task for increasing machining efficiency and economics. Selection of optimal machining parameters is often performed by integrating empirical models with traditional mathematical and meta-heuristic algorithms. Ability to deal with complex and multi-dimensional optimization problems resulted in growing interest on the application of meta-heuristic ...

One of the most important extensions of the capacitated vehicle routing problem (CVRP) is the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) where customers require simultaneous delivery and pick-up service. In this paper, we propose an effective ant colony optimization (EACO) which includes insert, swap and 2-Opt moves for solving VRPSPD that is different with common an...

in this article, multiple-product pvrp with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. a mathematical formulation was provided for this problem. each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. to solve the problem, two meta-heuristic methods...

the travelling salesmen problem (tsp) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. in this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally comes back to depot. solving this problem seems hard because program statement is simple and leads this problem belonging to np...