Improved behavioral analysis of fuzzy cognitive map models

Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach. © Springer International Publishing AG, part of Springer Nature 2018.Peer reviewe

Theoretical and practical convergence of a self-adaptive penalty algorithm for constrained global optimization

This paper proposes a self-adaptive penalty function and presents a penalty-based algorithm for solving nonsmooth and nonconvex constrained optimization problems. We prove that the general constrained optimization problem is equivalent to a bound constrained problem in the sense that they have the same global solutions. The global minimizer of the penalty function subject to a set of bound constraints may be obtained by a population-based meta-heuristic. Further, a hybrid self-adaptive penalty firefly algorithm, with a local intensification search, is designed, and its convergence analysis is established. The numerical experiments and a comparison with other penalty-based approaches show the effectiveness of the new self-adaptive penalty algorithm in solving constrained global optimization problems.The authors would like to thank the referees, the Associate Editor and the Editor-in-Chief for their valuable comments and suggestions to improve the paper. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Funda¸c˜ao para a Ciˆencia e Tecnologia within the projects UID/CEC/00319/2013 and UID/MAT/00013/2013.info:eu-repo/semantics/publishedVersio

Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making

Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis

Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting

Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods

Computer aided aggregate scheduling of machining and assembly systems by using directed graphs

Bu makalede imalat ve montaj sistemlerinde küme çizelgelemesinin yönlendirilmiş grafiklerle çözümü anlatılmıştır. Problemin çözümü için bir bilgisayar programı geliştirilmiş ve örnek bir uygulama problemi ile program ve yöntem gösterilmiştir.In this paper aggregate scheduling of machining and assembly systems by using directed graphs is considered. For solving the problem a computer program is developed and the working of the program is shown by a worked example

Fabrika organizasyonunda Hillier algoritmasının güncelleştirilmesi için bir girişim

Bu çalışmada, fabrika yerleşimi için Frederick S. Hillier tarafından önerilen prosedürü daha efektif bir hale getirebilmek için çaba sarfedilmiştir. Prosedür, bölümler arasındaki materyal taşınımının fiatını en aza indirecek şekilde, bölümlerin yerlerinin bulunmasını sağlamaktadır. Bu amaçla, Hillier'in algoritmasından yola çıkılarak, bir bilgisayar programı yazılmıştır. Geliştirilen yazılımın daha ideal sonuçlar verebildiği görülmüştür. Programa girdi olarak, toplam departman sayısı, arzu edilen organizasyon tipi (satır ve sütun sayısı), bölümler arasındaki malzeme akışları, ve bir başlangıç çözüm verilmektedir. Ayrıca bölümler arasındaki uzaklıklar bilgisayar ekranından girilebildiği gibi istenildiği takdirde önceden hazırlanmış veri dosyalardan okunabilmektedir. İyileştirme, algoritma tarafından koyulan kuralların gerektirdiği biçimde, bölümlerin birbirleriyle ikili olarak yer değiştirmesiyle sağlanmaktadır. Program oldukça hızlıdır ve optimum çözüme yakın bir çözüm önerisi ile bitirilmektedir. Program Borland C++ programlama dili kullanılarak, IBM uyumlu bir bilgisayarda yazılmıştır. Programın kullanımı örneklerle açıklanmış, sonuçlar Hillier algoritmasının sonuçlarıyla karşılaştırılmıştır.In this study, an effort has been made to enhance the procedure suggested by Frederick S. Hillier for plant layout analysis. It considers the development of relative positions of a number of departments with the objective of minimising the total material flow between those departments. For this purpose, a computer program has been written by utilising the rules given in the well known Hillier's algorithm and it has been shown that the developed software yields more idealised layout approaching the optimum solution. Upon inputting total number of facilities, desired number of rows and columns in the final layout, weighting flows between the facilities, and an initial solution, the program either allows the user to give distances between the locations manually, or takes them from a file stored previously in the memory. The improvement is achieved by interchanging the facilities among each other as proposed by the rules constructed within the algorithm. The program is terminated when a final solution for the layout is achieved. It is ver}' fast and approaches to the optimal solution.The program is written in Borland C++ programming language on an IBM compatible PC. The use of the program is given through specific examples. The results are compared with those of Hillier Procedure

A multi-agent based approach to dynamic scheduling with flexible processing capabilities

A multi-agent based system is proposed to simultaneous scheduling of flexible machine groups and material handling system working under a manufacturing dynamic environment. The proposed model is designed by means of Prometheus TM methodology and programmed in JACK TM agent based systems development environment. Each agent in the model is autonomous and has an ability to cooperate and negotiate with the other agents in the system. Due to these abilities of agents, the structure of the system is more suitable to handle dynamic events. The proposed dynamic scheduling system is tested on several test problems the literature and the results are quite satisfactory because it generates effective schedules for both dynamic cases in the real time and static problem sets. Although the model is designed as an online method and has a dynamic structure, obtained schedule performance parameters are very close to those obtained from offline optimization based algorithms. © 2015, Springer Science+Business Media New York