Identification of weights in multi-cteria decision problems based on stochastic optimization

Many scientific papers are devoted to solving multi-criteria problems using methods that find discrete solutions. However, the main challenge addressed by our work is the case when new decision-making variants have emerged which have not been assessed. Unfortunately, discrete identification makes it impossible to determine the preferences for new alternatives if we do not know the whole set of parameters, such as criteria weights. This paper proposes a new approach to identifying a multi-criteria decision model to address this challenge. The novelty of this work is using a discretization in the space of the problem to identify a continuous decisional model. We present a hybrid approach where the new alternative can be assessed based on stochastic optimization and the TOPSIS technique. The stochastic methods are used to find criteria weights used in the TOPSIS method. In that way, we get assessed easily each new alternative based only on the initial set of evaluated alternatives

TOWARDS RELIABLE DECISION-MAKING IN THE GREEN URBAN TRANSPORT DOMAIN

Operational research is a scientific discipline related to the decision theory that allows determining solutions for specific problems related to, for example, widely understood transport. Increasingly popular in this field are issues related to the domain of the green urban transport. In order to support the decision-making process in this area, methods of multi-criteria decision analysis (MCDA) are used more and more often. However, if we solve a specific problem using different MCDA methods, we get different rankings, as each method has a different methodological basis. Therefore, the challenge is how to make a reliable decision. This paper presents a numerical example from the green urban transport domain, which is solved by six different MCDA methods that return a complete ranking. We measure the similarity of these rankings using coefficients rw and WS, and then we propose a simple way of determining a compromise solution. The obtained compromise ranking is guaranteed to be the best match to the selected MCDA methods' rankings, which is proved in the paper. Finally, possible directions for further development work are identified

STUDY TOWARDS THE TIME-BASED MCDA RANKING ANALYSIS – A SUPPLIER SELECTION CASE STUDY

Decision-making processes increasingly use models based on various methods to ensure professional analysis and evaluation of the considered alternatives. However, the abundance of these methods makes it difficult to choose the proper method to solve a given problem. Also, it is worth noting whether different results can be obtained using different methods within a single decision problem. In this paper, we used three selected Multi-Criteria Decision Analysis (MCDA) methods called COMET, TOPSIS, and SPOTIS in order to examine how the obtained rankings vary. The selection of material suppliers was taken into consideration. The equal weights, entropy and standard deviation methods were used to determine the weights for criteria. Final preferences values were then compared with the WS similarity coefficient and weighted Spearman correlation coefficient to check the similarity of the received rankings. It was noticed that in the given problem, all of the methods provide highly correlated results, and the obtained positional rankings are not significantly different. However, practical conclusions indicate the need to look for improved solutions in the correct and accurate assessment of suppliers in a given period

Version [1.1]- [pyFDM: A python library for uncertainty decision analysis methods]

This paper describes an extension of the pyFDM library by extending the functionalities of the programming package with new Fuzzy Multi-Criteria Decision Analysis methods such as Combined Compromise Solution (CoCoSo), Stable Preference Ordering Towards Ideal Solution (SPOTIS), Weighted Aggregated Sum Product ASSessment (WASPAS), Weighted Product Model (WPM), and Weighted Sum Model (WSM). Furthermore, the proposed update includes new normalization techniques, new distance metrics, and defuzzification methods to allow users to examine the greater variety of research approaches in a Triangular Fuzzy environment. Furthermore, the update also extends with the implementations allowing for fuzzy calculations outside the multi-criteria field, which is allowed by the implementation of selected mathematical operations for Triangular Fuzzy Numbers. The opportunity to visualize the data within the fuzzy extension considered is also included. The extension of the pyFDM package broadens the scope of its usage in research approaches, making it a more suitable tool for multi-criteria decision analysis within the fuzzy environment

Handling decision-making in Intuitionistic Fuzzy environment: PyIFDM package

The introduction of fuzzy logic assumptions into Multi-Criteria Decision Analysis (MCDA) methods has broadened the application area of these techniques, increasing their practical potential. Due to their popularity, decision-makers need to have access to open and comprehensive tools to assist them in their decision-making process. In this paper, we propose a software library written in Python for multi-criteria computing in an uncertain environment. PyIFDM (Python Intuitionistic Fuzzy Decision Making) offers users access to selected Intuitionistic Fuzzy MCDA methods, normalization techniques, distance measures, score functions, or objective weighting methods. It enables users to build complex decision-making models regarding the uncertainties occurring in the problem

Support for Perimeter Border Protection Using Unmanned Ground Vehicle UGV

W artykule poruszono najważniejsze aspekty projektowania pojazdu bezzałogowego do realizacji zadań obserwacyjnych przy ochronie perymetrycznej granicy państwa. Przedstawiona została analiza warunków terenowych koniecznych do pokonywania przez pojazd bezzałogowy oraz opis kluczowych podzespołów pojazdu HUNTeR odpowiedzialnych za możliwość pracy w tego typu warunkach. Zawarto też wyniki badań weryfikujących założenia podstawowe projektu w zakresie pracy z maksymalną prędkością przejazdu.The article concerns the most important issues of designing an unmanned vehicle for the implementation of observation tasks in the protection of the perimeter of the state border. An analysis of the terrain conditions necessary for the unmanned vehicle to overcome and a description of the key components of the HUNTeR vehicle responsible for the ability to work in such conditions was presented. Also included were tests verifying the basic assumptions of the project in the field of operation at the maximum speed of travel

A New Method to Support Decision-Making in an Uncertain Environment Based on Normalized Interval-Valued Triangular Fuzzy Numbers and COMET Technique

Multi-criteria decision-making (MCDM) plays a vibrant role in decision-making, and the characteristic object method (COMET) acts as a powerful tool for decision-making of complex problems. COMET technique allows using both symmetrical and asymmetrical triangular fuzzy numbers. The COMET technique is immune to the pivotal challenge of rank reversal paradox and is proficient at handling vagueness and hesitancy. Classical COMET is not designed for handling uncertainty data when the expert has a problem with the identification of the membership function. In this paper, symmetrical and asymmetrical normalized interval-valued triangular fuzzy numbers (NIVTFNs) are used for decision-making as the solution of the identified challenge. A new MCDM method based on the COMET method is developed by using the concept of NIVTFNs. A simple problem of MCDM in the form of an illustrative example is given to demonstrate the calculation procedure and accuracy of the proposed approach. Furthermore, we compare the solution of the proposed method, as interval preference, with the results obtained in the Technique for Order of Preference by Similarity to Ideal solution (TOPSIS) method (a certain preference number)

An Attempt to Sustainable Cities and Society Evaluation - MCDA Based Approach

The new paradigm for economic growth, social equality and environmental protection named sustainable development (SD) was introduced into the international community at the end of the 20th century. However, there are still difficulties in reliably assessing a specific objectives of SD. Among them the attention of many researchers has been drawn to sustainable city and society goal. In this study, we focus on data from 2013 to 2017 from EU countries in the context of their sustainable cities and society assessment. We propose a new approach to evaluating sustainable cities and society. A MCDA method called COMET was adopted to measure sustainability level. The obtained results were compared with reference MCDA methods called TOPSIS and VIKOR. The similarity coefficients are used to examine the similarity of final rankings. The motivation to choose the COMET method was a set of its abilities in opposite to the existing MCDA method, COMET is a rank reversal free method. Additionally, as a result of COMET model exploitation, the whole domain model is identified

Input data preprocessing for the MCDM model: COPRAS method case study

Multi-Criteria Decision-Making (MCDM) methods are widely used in many areas and disciplines. At the same time, they give the strong methodical background of many decision support systems. However, an important and current research issue remains the obtaining reliable results of individual MCDM methods. In this paper, the influence of the used decision matrix normalization method on the obtained rankings is studied on the example of applying the COPRAS method. Five methods are used to normalize matrices of different sizes. The rankings obtained by performing multiple assessments of alternatives are then compared using selected similarity coefficients. The influence of normalization on the final rankings is noticed, which is confirmed by diverse correlations

How to Apply Fuzzy MISO PID in the Industry? An Empirical Study Case on Simulation of Crane Relocating Containers

The proportional-integral-derivative (PID) algorithm automatically adjusts the control output based on the difference between a set point and a measured process variable. The classical approach is broadly used in the majority of control systems. However, in complex problems, this approach is not efficient, especially when the exact mathematical formula is difficult to specify. Besides, it was already proven that highly nonlinear situations are also significantly limiting the usage of the PID algorithm, in contrast to the fuzzy algorithms, which often work correctly under such conditions. In the case of multidimensional objects, where many independently operating PID algorithms are currently used, it is worth considering the use of one fuzzy algorithm with many-input single-output (MISO) or many-input many-output (MIMO) structure. In this work, a MISO type chip is investigated in the study case on simulation of crane relocating container with the external distribution. It is an example of control objects that due to badly conditioned dynamic features (strong non-linearities) require the operator’s intervention in manual or semi-automatic mode. The possibility of fuzzy algorithm synthesis is analyzed with two linguistic variable inputs (distance from −100 to 500 mm and angle from −45° to 45°). The output signal is the speed which is modelled as a linguistic power variable (in the domain from −100% to 100%). Based on 36 fuzzy rules, we present the main contribution, the control system with external disturbance, to show the effectiveness of the identified fuzzy PID approach with different gain values. The fuzzy control system and PID control are implemented and compared concerning the time taken for the container to reach the set point. The results show that fuzzy MISO PID is more effective than the classical one because fuzzy set theory helps to deal with the environmental uncertainty. The container’s angle deviations are taken into consideration, as mitigating them and simultaneously maintaining the fastest speed possible is an essential factor of this challenge