evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

The goal of this chapter is to introduce the key algorithms and theory that constitute the core of Evolutionary computation. The principles and foundations of a basic genetic Algorithm are described in detail. In addition, a separate section discusses extensions to the simple Genetic Algorithm, such as reened crossover, mutation and selection schemes. and real coded representations. The chapter...

This paper presents a new methodology using fuzzy and Real Coded Genetic Algorithm (RCGA) for the placement of capacitors on the primary feeders of the radial distribution systems to reduce the power losses and to improve the voltage profile. A two-stage methodology is used for the optimal capacitor placement problem. In the first stage, fuzzy approach is used to find the optimal capacitor loca...

Requirement conversion (RC) is an important activity in product customized design. Nowadays, the RC process mostly driven by designers’ knowledge, model passive to dynamic customer requirements, and behavior a black box customers. Digital twin (DT) characterized as self-reinforcing mechanism mirroring between physical virtual spaces, which powerful addressing these challenges for RC. This paper...

This paper proposes a new methodology for the optimal allocation and sizing of Embedded Generation (EG) employing Real Coded Genetic Algorithm (RCGA) to minimize the total power losses and to improve voltage profiles in the radial distribution networks. RCGA is a method that uses continuous floating numbers as representation which is different from conventional binary numbers. The RCGA is used ...

Asso. Prof.,Dept. of Mech. Engg. G.I.E.T, Rajahmundry, A.P, India DGM (Retd.), B.H.E.L, R&D, Balanagar, Hyderabad, A.P, India Abstract Surface roughness, an indicator of surface quality is one of the most specified customer requirements in a machining process. For efficient use of machine tools, optimum cutting parameters (speed, feed and depth of cut) are required. So it is necessary to find a...

Orthogonal least trimmed absolute deviation (OLTAD) estimator of the multiple linear errors-in-variables (EIV) model is presented. We show that the OLTAD estimator has the high breakdown point and appropriate properties. A new decimal-integer-coded genetic algorithm(DICGA) and Fast-OLTAD method for solving OLTAD estimators are also proposed. Computational experiments of the OLTAD estimator of t...

long-term settlement of msw landfills is a complex process, which is explained by the following two mechanisms: (1) the mechanical long-term compression of degradable organic solids (dos) and un-degradable organic solids (udos); and (2) the decomposition-based compression of the dos. based on these two distinct settlement mechanisms, in this study, the authors propose a new estimation model to ...