Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In mos...

Pareto archived dynamically dimensioned search (PA-DDS) has been modified to solve combinatorial multi-objective optimization problems. This new PA-DDS algorithm uses discrete-DDS as a search engine and archives all non-dominated solutions during the search. PA-DDS is also hybridized by a general discrete local search strategy to improve its performance near the end of the search. PA-DDS inheri...

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...