Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques

Exact optimization algorithms are not able to provide an appropriate solution in solving optimization problems with a high-dimensional search space. In these problems, the search space grows exponentially with the problem size therefore; exhaustive search is not practical. Also, classical approximate optimization methods like greedy-based algorithms make several assumptions to solve the problems. Sometimes, the validation of these assumptions is difficult in each problem. Hence, meta-heuristic algorithms which make few or no assumptions about a problem and can search very large spaces of candidate solutions have been extensively developed to solve optimization problems these days. Among these algorithms, population-based meta-heuristic algorithms are proper for global searches due to global exploration and local exploitation ability. In this paper, a survey on meta-heuristic algorithms is performed and several population-based meta-heuristics in continuous (real) and discrete (binary) search spaces are explained in details. This covers design, main algorithm, advantages and disadvantages of the algorithms.

http://home.ijasca.com/data/documents/IJASCA07_REVISED.pdf

A review of population-based meta-heuristic algorithm

A new PID controller for resistant differential control against load disturbance is introduced that can be used for load frequency control (LFC) application. Parameters of the controller have been specified by using imperialist competitive algorithm (ICA). Load disturbance, which is due to continuous and rapid changes of small loads, is always a problem for load frequency control of power systems. This paper introduces a new method to overcome this problem that is based on filtering technique which eliminates the effect of this kind of disturbance. The object is frequency regulation in each area of the power system and decreasing of power transfer between control areas, so the parameters of the proposed controller have been specified in a wide range of load changes by means of ICA to achieve the best dynamic response of frequency. To evaluate the effectiveness of the proposed controller, a three-area power system is simulated in MATLAB/SIMULINK. Each area has different generation units, so utilizes controllers with different parameters. Finally a comparison between the proposed controller and two other prevalent PI controllers, optimized by GA and Neural Networks, has been done which represents advantages of this controller over others.

A robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems.

Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition

Optimum design of skeletal structures using imperialist competitive algorithm

Purpose – This paper aims to describe colonial competitive algorithm (CCA), a novel socio‐politically inspired optimization strategy, and how it is used to solve real world engineering problems by applying it to the problem of designing a multivariable proportional‐integral‐derivative (PID) controller Unlike other evolutionary optimization algorithms, CCA is inspired from a socio‐political process – the competition among imperialists and colonies In this paper, CCA is used to tune the parameters of a multivariable PID controller for a typical distillation column processDesign/methodology/approach – The controller design objective was to tune the PID controller parameters so that the integral of absolute errors, overshoots and undershoots be minimized This multi‐objective optimization problem is converted to a mono‐objective one by adding up all the objective functions in which the absolute integral of errors is emphasized to be reduced as long as the overshoots and undershoots remain acceptableFindin

https://www.icasite.info/icasite/ica_papers/new_code/icapap_2008_en_esmae_colonialco.pdf

Colonial competitive algorithm A novel approach for PID controller design in MIMO distillation column process

In this paper a novel socio-politically inspired optimization strategy, an Imperialist Competitive Algorithm, is applied to the problem of designing a fuzzy controller. The goal is to design a controller to enhance the transient and steady state behaviour of the system output. Having fixed the rule base of the fuzzy system, the controller is designed through determining the membership functions of the input and output variables. The design method is applied to a model of vehicle. The inputs of the fuzzy system are velocity of the vehicle and the sloop of the road. The fuzzy controller controls the speed of the vehicle by adjusting the amount of gas into vehicle engine. Comparison results among the designed controller and the controller designed by the expert show that the controller obtained by Imperialist competitive algorithm has better performance than the expert controller. Keywords: Fuzzy Controller, Imperialist Competitive Algorithm (ICA), Membership Function, Vehicle

Esmaeil Atashpaz Gargari

Papers

Colonial competitive algorithm A novel approach for PID controller design in MIMO distillation column process

Vehicle Fuzzy Controller Design Using Imperialist Competitive Algorithm