Journal of Intelligent & Fuzzy Systems - Volume 29, issue 5

Authors: Rezai, Hamid Reza | Mohammadi, Sirus | Bagheri, Mahmod Zade | Moghimi, Rohalla

Article Type: Research Article

Abstract: This paper proposes a new stochastic framework to solve the practical economic dispatch (ED) problem considering the penetration of wind turbines (WTs). The proposed stochastic method is constructed based on krill herd (KH) algorithm to search the problem space optimally. Since the output power of WT is neither stable nor continues, point estimate method (PEM) with 2m scheme is used to model the uncertainty effects. In addition to the traditional constraints, the practical ED includes valve-loading effect, multi-fuel option, prohibited operating zone (POZ), ramp rate limit and spinning reserve. According to the high complexity and nonlinearity of the problem, …a new version of KH called Modified Levy Krill Herd (MLKH) is suggested to solve the problem optimally. The satisfying performance of the problem is examined on two standard test systems and is compared with some of the recent well-know methods in the area successfully. Show more

Keywords: Economic dispatch, point estimate method, Levy Krill Herd, practical constraints

DOI: 10.3233/IFS-151691

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2159-2167, 2015

Authors: Rafe, Vahid | Paiandeh, Zahra | Nikanjam, Amin

Article Type: Research Article

Abstract: Harmony Search (HS), as a novel optimization algorithm, is interesting for researchers because of its simplicity and appropriate efficiency. This algorithm has been applied to different continuous optimization problems leading to successful results. The parameter setting significantly impacts the performance of Harmony Search, similar to other meta-heuristics. In order to enhance this algorithm and facilitate the task of parameter setting, a hybrid approach is introduced in this paper. The harmony algorithm is improved by combining with the Differential Evolution (DE), as a successful evolutionary optimization algorithm which have been yielded admissible results in solving difficult problems. The new algorithm is …tested on some well-known benchmark functions. The results show that the new hybrid algorithm has superior performance in comparison to the original Harmony Search and a modified version which is called Improved Harmony Search. Show more

Keywords: Continuous optimization, harmony search, differential evolution, hybrid algorithms

DOI: 10.3233/IFS-151692

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2169-2176, 2015

Authors: Li, Zhen-Bo | Liu, Hua-Wen

Article Type: Research Article

Abstract: In this paper, two classes of generalized (U , N )-implications derived from commutative semi-uninorms and pseudo-uninorms are investigated. Then some properties of U I ,N operations derived from implications are explored. Last the necessary and sufficient conditions such that a (U CS , N )-operation (or (U P , N )-operation) is an implication are given out.

Keywords: Fuzzy connective, fuzzy implication, (US, N)-implication, commutative semi-uninorm, pseudo-uninorm

DOI: 10.3233/IFS-151693

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2177-2184, 2015

Authors: Sedaghati, Reza | Honarmand, Sima | Nemati, Yaser

Article Type: Research Article

Abstract: This paper proposes a new stochastic method based on u-transform (UT) to capture the uncertainties of the reconfiguration in a correlated environment. The proposed stochastic framework makes use of the idea covariance matrix to reach this goal. Also, in order to reach the maximum efficiency of the reconfiguration strategy, reliability indices are considered along with the traditional targets in the multi-objective framework. Therefore, the objective functions to be optimized are System Average Interruption Frequency Index (SAIFI), Average Energy Not Supplied (AENS), total active power losses and the total network costs. Since the problem investigated is a complex, nonlinear optimization problem, …a new optimization method based on krill herd algorithm (KH) is introduced. In addition, a new modification method is proposed for the KH algorithm to improve its total search ability. The feasibility and performance of the proposed method are examined on the IEEE standard test system. Show more

Keywords: U-transform, multi-objective reconfiguration, krill herd algorithm

DOI: 10.3233/IFS-151694

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2185-2192, 2015

Authors: Zhao, Xinqiu | Wang, Xi | Sun, Hao | Wang, Liping | Ma, Mingming

Article Type: Research Article

Abstract: Differential evolution algorithm (DE) has yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization issues. Due to its simple structure, fast convergence and strong robustness, DE has received increasing attention and wide application in a variety of fields. We propose a novel differential evolution approach (SE-DE) which uses an external archive for opposition-based learning, by this way, more high quality solutions can be selected for candidate solutions. In addition, the mutation factor (F ) is adaptively controlled based on the success of offspring/trial solutions generated. An optimization factor α is proposed to select the crossover strategy, a combination …of binomial and exponential crossover can effectively balance the exploration and exploitation ability of the algorithm. The performance of SE-DE is compared with the other five DE algorithms including DE, SADE, ODE, NDE and MDE-pBX. The comparison is carried out for a set of 30-, 50- and 100-dimensional test functions from CEC2005. The results show that our algorithm is better than, or at least comparable to, the algorithms from other literature. Show more

Keywords: Differential evolution (DE), self adaptive, external archive, global optimization, unconstrained single objective optimization

DOI: 10.3233/IFS-151695

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2193-2204, 2015

Authors: Liu, Zhengmin | Liu, Peide

Article Type: Research Article

Abstract: Normal intuitionistic fuzzy numbers (NIFNs), which express their membership degree and non-membership degree as normal fuzzy numbers, can better character normal distribution phenomena existing in the real world. In this paper, we investigate the multiple attribute decision making problems with normal intuitionistic fuzzy information. Firstly, we introduce some operational laws, score function and accuracy function of NIFNs. Then, motivated by the ideal of Bonferroni mean, which can capture the interrelationship between input arguments, we develop some normal intuitionistic fuzzy aggregation operators, including the normal intuitionistic fuzzy Bonferroni mean (NIFBM) operator, the normal intuitionistic fuzzy weighted Bonferroni mean (NIFWBM) operator, the …normal intuitionistic fuzzy geometric Bonferroni mean (NIFGBM) operator and the normal intuitionistic fuzzy geometric weighted Bonferroni mean (NIFGWBM) operator; and discuss some desirable properties of these operators. Furthermore, based on these operators, we propose a new approach for the multiple attribute group decision making under normal intuitionistic fuzzy environment. Finally, we give a numerical example to illustrate the effectiveness and feasibility of the developedapproach. Show more

Keywords: Multiple attribute group decision making, normal intuitionistic fuzzy numbers, Bonferroni mean, normal intuitionistic fuzzy Bonferroni mean operator, normal intuitionistic fuzzy geometric Bonferroni mean operator

DOI: 10.3233/IFS-151696

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2205-2216, 2015

Authors: Wen, Meilin | Qin, Zhongfeng | Kang, Rui | Yang, Yi

Article Type: Research Article

Abstract: Facility location-allocation (FLA) problem has been widely studied by operational researchers due to its many practical applications. In real life, it is usually very hard to present the customers’ demands in a precise way and thus they are regarded to be uncertain. Since the uncertain demands can be estimated from historical data, researchers tried to describe FLA problem under stochastic environment. Although stochastic models can cater for a variety of cases, they are not sufficient to describe many other situations, where the probability distribution of customers’ demands may be unknown or partially known. Instead we have to invite some domain …experts to evaluate their belief degree that each event will occur. This paper will consider the capacitated FLA problem under small sample or no-sample cases and establish an uncertain expected value model based on uncertain measure. In order to solve this model, the simplex algorithm, Monte Carlo simulation and a genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, a numerical example is presented to illustrate the uncertain model and the algorithm. Show more

Keywords: Location-allocation problem, uncertainty theory, uncertain measure, uncertain programming, genetic algorithm

DOI: 10.3233/IFS-151697

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2217-2226, 2015

Authors: Yadav, Harikesh Bahadur | Yadav, Dilip Kumar

Article Type: Research Article

Abstract: Construction of membership functions from numerical data is very important in various applications of the fuzzy set theory. In last two decade, many methods of membership function generation have been developed. Majority of the methods are application domain dependent and complex. In this paper, a simple method for the construction of membership functions from numerical data is proposed. To validate the proposed method, commonly used and suggested evaluation measures: average error rate, mean magnitude of relative error (MMRE), balanced mean magnitude of relative error (BMMRE), and coefficient of determination (R2 ), have been taken. The validating results show that proposed …method has a higher accuracy than existing methods. The sensitivity analysis has been performed to analyze the impact of input variable on the output variable. Show more

Keywords: Membership function, fuzzy set, fuzzy inference system, k-means clustering, training data

DOI: 10.3233/IFS-151698

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2227-2233, 2015

Authors: Zhang, Xin | Liu, Peide | Wang, Yumei

Article Type: Research Article

Abstract: On the basis of Frank operators, the operational rules of intuitionistic fuzzy numbers are redefined, then the intuitionistic fuzzy Frank power average operator (IFFPA), intuitionistic fuzzy Frank power weighted average operator (IFFPWA) and intuitionistic fuzzy Frank power ordered weighted average operator (IFFPOWA) are proposed by combining Frank operations and power aggregation operators. At the same time, some desirable properties of these operators, such as idempotency, commutativity and boundedness, are studied, and some special cases are analyzed. Furthermore, with respect to multiple attribute group decision making (MAGDM) problems in which attribute values take the form of the intuitionistic fuzzy numbers, two …group decision making methods based on IFFPWA and IFFPOWA operators are developed. Finally, an illustrative example is given to verify the proposed methods and to demonstrate their practicality and effectiveness. Show more

Keywords: Intuitionistic fuzzy number, Frank operator, power average operator, multiple attribute group decision making

DOI: 10.3233/IFS-151699

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2235-2246, 2015

Authors: Razavi, Seyedeh Fatemeh | Sajedi, Hedieh

Article Type: Research Article

Abstract: The Gravitational Search Algorithm (GSA) has been proposed for solving continues problems based on the law of gravity. In this paper, we propose a Cognitive Discrete GSA (called CDGSA) for solving 0-1 knapsack problem. The GSA has used a function of time to determine the number of the best particles for attracting others in each time, while our main idea is based on attracting each particle with two cognitive and social components. The cognitive component contains the best position of the particles up to now, while the social component contains the particle with the best position in the whole of …the system at the current time and the particles with the best position in the neighborhood. In the other words, the cognitive component is such an appropriate actuator for embedding in the intelligent agents like robots. Such intelligent agent or robot is guided in the right direction with the help of its best previous position. Finally, by introducing discrete version of this idea, the efficiency of the proposed algorithm is measured for 0-1 knapsack problem. Experimental results on some benchmark and high dimensional problems illustrate that the proposed algorithm has gained the better accuracy in comparison of the other similar methods. Show more

Keywords: Cognitive component, discrete gravitational search algorithm (DGSA), knapsack problem, social component

DOI: 10.3233/IFS-151700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2247-2258, 2015