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Abstract: Accurate kinetic models are of great significance for the simulation and analysis for hydrogen fuel cells. The proton exchange membrane (PEM) fuel cell is a complex nonlinear, multi-variable system. The mathematical modeling of PEM fuel cell usually leads to nonlinear parameter estimation problems which often contain more than one minimum. In this paper, a novel bio-inspired P systems based optimization algorithm, named BIPOA, is proposed to solve PEM fuel cell model parameter estimation problems. In BIPOA, the nested membrane structure and new rules such as adaptive mutation rule, partial migration rule and autophagy rule are combined to improve the algorithm''s global search capacities and convergence accuracy. Studies on some benchmark test functions indicate that the BIPOA outperforms the other two methods (PSOPS and GAs) in both convergence speed and accuracy. In addition, experimental results reveal that the model predictive outputs are in better agreement with the actual experimental data. Therefore, the BIPOA is a helpful and reliable technique for estimating the PEM fuel cell model parameters and is available to other complex parameter estimation problems of fuel cell models. [Copyright &y& Elsevier]

Abstract: The railroad blocking problem is one of the most important decision in freight railroads. The objective of this problem is to minimize the costs of delivering all commodities by deciding which inter-terminal blocks to build and specifying the assignment of commodities to these blocks, while observing limits on the number and aggregate volume of the blocks assembled at each terminal. This paper presents a metaheuristic algorithm based on ant colony optimization for solving this problem. To evaluate the efficiency of the proposed algorithm and the quality of solutions, experimental analysis is conducted, using several simulated test problems. The results on the test problems are compared with those of solution generated with CPLEX software. The results show high efficiency and effectiveness of the proposed algorithms. The solution method is applied to build car blocking plan in Islamic Republic of Iran Railways. By applying the presented model, Iran Railways can reduce the operational cost considerably and save the time in shipping the freights as well. [Copyright &y& Elsevier]

Abstract: This paper aims to show the use of the response surface methodology (RSM) in size optimization of an autonomous PV/wind integrated hybrid energy system with battery storage. RSM is a collection of statistical and mathematical methods which relies on optimization of response surface with design parameters. In this study, the response surface, output performance measure, is the hybrid system cost, and the design parameters are the PV size, wind turbine rotor swept area and the battery capacity. The case study is realized in ARENA 10.0, a commercial simulation software, for satisfaction of electricity consumption of the global system for mobile communications (GSM) base station at Izmir Institute of Technology Campus Area, Urla, Turkey. As a result, the optimum PV area, wind turbine rotor swept area, and battery capacity are obtained to be 3.95m2, 29.4m2, 31.92kWh, respectively. These results led to $37,033.9 hybrid energy system cost, including auxiliary energy cost. The optimum result obtained by RSM is confirmed using loss of load probability (LLP) and autonomy analysis. [Copyright &y& Elsevier]

Abstract: This paper presents an integrated simulation, multivariate analysis and multiple decision analysis for railway system improvement and optimization. Furthermore, the integrated model is based on data envelopment analysis (DEA) and analytical hierarchy process (AHP) that is integrated with computer simulation . The integrated DEA and AHP simulation model can be used for selecting optimum alternatives by considering multiple quantitative and qualitative inputs and outputs. First, computer simulation is used to model verify and validate the system being studied. Second, AHP methodology determines the weight of any qualitative criteria (input or outputs). Finally, the DEA model is used to solve the multi-objective model to identify the best alternative(s) and also to identify the mechanism to optimize current system. An 800-km train route system was selected as the case of this study. Visual SLAM language was used to develop the simulation model of the railway system. The objective of simulation model is to increase reliability related to the time table of the passenger trains, to decrease average traverse time of passenger trains and to decrease average traverse time of cargo trains. In addition, for multivariate assessment of the alternatives by DEA, safety and cost factors are derived and considered from an AHP analysis. Previous studies use simulation and DEA based on quantitative variables for identification of the most efficient scenarios, while this study considers both quantitative and qualitative variables for efficiency assessment and performance optimization by integration of simulation, DEA and AHP. This is quite important for systems where some of their performance measures are qualitative such as railway and production systems. [Copyright &y& Elsevier]

Abstract: Torczon and several persons have designed pattern search methods for unconstrained optimization problem, bound constrained, and linearly constrained optimization problems. In this paper, we shall consider linear equality constrained problems as unconstrained ones using generalized pattern search algorithm, except for a feasible starting point. [Copyright &y& Elsevier]