Optimization of the complete manufacturing and supply process has become a critical ingredient for gaining a competitive advantage. This article provides a unified mathematical framework for modeling manufacturing cell configuration and raw material supplier selection in a two-level supply chain network. The commonly used manufacturing design parameters along with supplier selection and a subco...

In this study simulation and optimization of an industrial acetylene hydrogenation reactor was studied. Three well known kinetic models were used for a nearly similar catalyst to predict the industrial data. Due to the complexity of the reactions, none of the offered kinetic models could be considered as an exact kinetic model and it is necessary to determine the kinetic parameters. One of the ...

In this paper a narrative approach for designing FIR low pass filter is presented by practicing hybrid technique of Swine Influenza Model based Optimization (SIMBO) and Genetic Algorithm (GA). Premature convergence was the major difficulty faced by SIMBO algorithm individually in FIR filter design. To address this problem, a hybrid SIMBO-GA is proposed in this paper. GA is used to help SIMBO es...

Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. ...

This paper presents a massively parallel Genetic Algorithm – Pattern Search (GA-PS) with graphics hardware acceleration on bound constrained nonlinear optimization problems. The objective of this study is to determine the effectiveness of using Graphics Processing Units (GPU) as a hardware platform for Genetic Algorithms (GA). The global search of the GA is enhanced by a local Pattern Search (P...

Engineering design studies can often be cast in terms of optimization problems. However, for such an approach to be worthwhile, designers must be content that the optimization techniques employed are fast, accurate and robust. This paper describes recent studies of convergence and robustness problems found when applying genetic algorithms (GAS) to the constrained, multi-peak optimization proble...

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing pro...

Since the publication of our recently developed mode-pursing sampling (MPS) method, questions have been asked on its performance as compared with traditional global optimization methods such as genetic algorithm (GA), and when to use MPS as opposed to GA. This work aims to provide an answer to these questions. Similarities and distinctions between MPS and GA are presented. Then MPS and GA are c...

This paper presents a hybrid optimization algorithm based on a modified genetic algorithm (GA). The algorithm includes two stages. In the first stage, a global search is carried out over the design search space using a modified GA. In the second stage, a local search is executed that is based on GA solution using a discretized form of Hooke and Jeeves method. The modifications on basic GA inclu...

The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorithm (GA) is one of the most useful algorithms for solving this problem. In this paper a conventional GA is compared with an improved hybrid GA in solving TSP. The improved or hybrid GA consist of conventional GA and two local optimization strategies. The first strategy is extracting all sequential ...