Hybridizing metaheuristic approaches becomes a common way to improve the efficiency of optimization methods. Many hybridizations deal with the combination of several optimization methods. In this paper we are interested in another type of hybridization, where datamining approaches are combined within an optimization process. Hence, we propose to study the interest of combining metaheuristics an...

Logistics in natural disasters or emergencies involve highly complicated optimization problems with diverse characteristics. The contribution of the present paper is twofold. First, it introduces a multi-period model aiming to minimize the shortages of different relief products in a number of affected areas. The relief products are transported via multiple modes of transportation from dispatch ...

We propose a control design scheme that aims to prevent undesirable liquid outpouring and suppress sloshing during the forward and backward tilting phases of the pouring process, for the case of liquid containers carried by manipulators. The proposed scheme combines a partial inverse dynamics controller with a PID controller, tuned with the use of a “metaheuristic” search algorithm. The “metahe...

The goal of the thesis is to study the behavior of the ant colony optimization metaheuristic under uncertain conditions. We choose the probabilistic traveling salesman problem (PTSP) as a test-bed amongst stochastic optimization problems, in much the same way as the traveling salesman problem (TSP) has been considered a standard amongst deterministic optimization problems. Given a set of cities...

-The ant colony optimization takes insipiration from the foraging behavior of some ant species.These ants deposits pheromone on the ground in order to make some suitable path that should be followed by other members of the colony.The goal of this paper is to introduce ant colony optimization and to survey its most notable applications.In this paper we focus on some research efforts directed at ...

The Berth Allocation Problem aims at assigning and scheduling incoming vessels to berthing positions along the quay of a container terminal. This problem is a well-known optimization problem within maritime shipping. For solving it, we propose two POPMUSIC (Partial Optimization Metaheuristic Under Special Intensification Conditions) approaches that incorporate an existing mathematical programmi...

A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. It is a multi-start or iterative process, in which each GRASP iteration consists of two phases, a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, numerous p...

In recent years, there has been an increasing interest in parallel computing. In parallel computing, multiple computing resources are used simultaneously in solving a problem. There are multiple processors that will work concurrently and the program is divided into different tasks to be simultaneously solved. Recently, a considerable literature has grown up around the theme of metaheuristic alg...

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA's results are compar...

Transportation Network Design Problem (TNDP) aims to select the best project sets among a number of new projects. Recently, metaheuristic methods are applied to solve TNDP in the sense of finding better solutions sooner. PSO as a metaheuristic method is based on stochastic optimization and is a parallel revolutionary computation technique. The PSO system initializes with a number of random solu...