This paper proposes an approach which is based on a multi objective genetic algorithm to resolve the vehicles routing problem with time windows (VRPTW). The context of this problem is to plan a set of routes to serve heterogeneous demands respecting several constraints (only one depot, vehicles limited capacity, windows of time). We used an approach based on a multi-objective optimization to re...

Received Jan 24, 2017 Revised May 4, 2017 Accepted Jun 10, 2017 In recent decades, one of the main management’s concerns of professional engineers is the optimal integration of various types of renewable energy to the grid. This paper discusses the optimal allocation of one type of renewable energy i.e. wind turbine to the grid for enhancing network’s performance. A multi-objective function is ...

Today, sustainable development is one of the important issues in regard to the economy of a country. This issue magnifies the necessity for increased scrutiny towards issues such as environmental considerations and product recovery in closed-loop supply chains (CLSCs). The most important motivational factors influencing research on these topics can be considered in two general groups: environme...

The Combined Heat and Power Economic Emission Load Dispatch (CHPEED) is an optimization problem to minimize the cost and emission while ensuring the fulfilling the power and heat demand and feasible constraints. This paper presents Particle Swarm Optimization (PSO) technique and other to solve CHPEED with bounded feasible operating region. The main potential of this technique is that it proper ...

Although population-based algorithms are robust in solving Multi-objective Optimization Problems (MOP), they often require a large number of function evaluations. In contrast, individual-solution based algorithms are fast but can be stuck in local minima. To solve these problems, we introduce a fast and adaptive local search algorithm for MOP. Our algorithm is an individual-solution algorithm w...

in this paper, lift and drag coefficients were numerically investigated using numeca software in a set of 4-digit naca airfoils. two metamodels based on the evolved group method of data handling (gmdh) type neural networks were then obtained for modeling both lift coefficient (cl) and drag coefficient (cd) with respect to the geometrical design parameters. after using such obtained polynomial n...

Grinding robots are widely used in the automotive, mechanical processing, aerospace industries, among others, due to their strong adaptability, high safety and intelligence. The grinding process parameters main factors that affect quality efficiency of robots. However, it is difficult obtain optimal combination only by manual experience. This study proposes an artificial intelligence-based meth...

Coastal areas are particularly vulnerable to flooding from heavy rainfall, sea storm surge, or a combination of the two. Recent studies project higher intensity and frequency rains, progressive level rise continuing over next decades. Pre-emptive optimal flood defense policies that adaptively address climate change needed. However, future projections have significant uncertainty due multiple fa...

Evolutionary Algorithms are recognized to be efficient to deal withMulti-objective Optimization Problems(MOPs) which are difficult to be solved with traditional methods. Here a newMulti-objective Optimization Evolutionary Algorithm named DGPS which is compound with Geometrical Pareto Selection Method (GPS), Weighted SumMethod (WSM) and Dynamical Evolutionary Algorithm (DEA) is proposed. Some fa...