In this paper we have developed a new technique to determine optimal solution to box pushing problem by two robots . Non-Dominated sorting genetic algorithm and Biogeography-based optimization algorithm are combined to obtain optimal solution. A modified algorithm is developed to obtain better energy and time optimization to the box pushing problem.

The modeling process is to find a parametric model whose dynamic behavior close to that process. This model will be used to make predictions of the process output, or to simulate the process in a control system...etc. In this work we used RBF neural networks for modeling nonlinear systems. Generally the problem in neural networks is often to find a better structure. We propose in this work a me...

This work addresses the research and development (R&D) of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this work focus is AIDA-CMK, by enhancing AIDA-C with a new multi-objective multi-constraint optimization kernel. AIDA-C is the circuit optimizer component of AIDA, an electronic design automation framework fully developed in-house. The prop...

The resolution of the environmental/economic dispatch (EED) problem using the different methods which are proposed in literature consumes an important computing time. Thus, the present paper deals with a technique based on two steps to solve the EED problem of electric energy power in real-time for forecast load curve. The first step uses the NSGAII approach (Non-dominated Sorting Genetic Algor...

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...

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...

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...