designing of a pid controller is a very common method for industrial process control and due to its very simple and efficient function; it is used in a wide variety of industrial applications. pid controller to reduce the steady state error and dynamic response of the system is used. pid controller design is an inevitable problem in setting the coefficients need to try a lot of trial and error,...

Article history: Received 8 December 2015 Received in revised form 5 November 2016 Accepted 11 November 2016 Available online xxxx Delimiting urban growth boundaries (UGBs) has been generally regarded as a regulatorymeasure for controlling chaotic urban expansion. There are increasing demands for delimiting urban growth boundaries in fast growing regions in China. However, existingmethods for d...

The Boolean Satisfiability Problem (BSAT) is one of the most important decision problems in mathematical logic and computational sciences for determining whether or not a solution to formula.. Hopfield neural network (HNN) major type artificial (NN) popularly known it used solving various optimization based on its energy minimization machinism. existing models that incorporate standalone projec...

The global demand for agricultural products is surging due to population growth, more meat-based diets, and the increasing role of bioenergy. Three strategies can increase agricultural production: (1) expanding agriculture into natural ecosystems; (2) intensifying existing farmland; or (3) recultivating abandoned farmland. Because agricultural expansion entails substantial environmental trade-o...

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...

the multiple traveling salesman problem (mtsp) is a generalization of the famous traveling salesman problem (tsp), where more than one salesman is used in the solution. although the mtsp is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. this paper presents an efficient and evolutionary optimization algorith...

an evolutionary structural optimization (eso) method is used for plastic design of frames. based on safe theorems some criteria are derived and made an effort to satisfy them during the optimization process. in this regard, equilibrium is checked and yield condition is gradually satisfied during the optimization process. in this method, the amount of used material and the stiffness for each ele...

the present study is concerned with the simultaneous optimization of the size of components and the arrangement of connections for performance-based seismic design of low-rise spsws. design variables include the size of beams and columns, the thickness of the infill panels, the type of each beam-to-column connection and the type of each infill-to-boundary frame connection. the objective functio...

this paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. portfolio optimization problem is a quadratic programming model and, changes to np-hard if the number of assets and constraints has increased, and it cannot be solved using common mathematical methods in a reasonable time. therefore, a heuristic or meta-heuristic algorithm should b...