This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability by considering to minimize the air pollution and maximize the social welfare as its objectives. This m...

Static Var compensator (SVC) is one of flexible AC transmission system (FACTS) elements mainly used for reactive power and voltage control in power systems. This paper deals with multi-modal electromechanical oscillations damping in the presence of severe disturbances. These oscillations include local modes, interarea modes and inter-plant modes. To enhance the damping of the oscillations, a co...

Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity, effectiveness and minimum involvement of the user. This article develops a multi-objective variation of the Nelder-Mead simplex method and combines it with NSGA-II in order to improve the quality and spread of the solutio...

The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...

one main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. this paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. indeed, the nature of products is considered different and hub capacity constraint is also applied. due to ...

The application of stochastic methods in engineering research and optimization has been increasing over the past few decades. Ant Colony Optimization, in particular, has been attracting growing attention as a promising approach both in discrete and continuous domains. The present work proposes a multiobjective Ant Colony Optimization for continuous domains showing good convergence properties an...

In this paper, we propose an efficient approach to design optimization of analog circuits that is based on the reinforcement learning method. In this work, Multi-Objective Learning Automata (MOLA) is used to design a two-stage CMOS operational amplifier (op-amp) in 0.25μm technology. The aim is optimizing power consumption and area so as to achieve minimum Total Optimality Index (TOI), as a new...