scholarly journals A Two-sided Matching Decision-making Approach based on PROMETHEE Under the Probabilistic Linguistic Environment

2021 ◽  
Author(s):  
Xiang Jia ◽  
Yingming Wang
Keyword(s):  
Decision Making ◽  
Lagrange Function ◽  
Preference Ranking ◽  
Matching Problem ◽  
Matching Problems ◽  
Objective Model ◽  
Intelligent Technology ◽  
Net Flows ◽  
Two Sides ◽  
Single Objective

Abstract Matching problems in daily life can be effectively solved by two-sided matching decision-making (TSMDM) approaches. The involved matching intermediary is to match two sides of subjects. This paper proposes a TSMDM approach based on preference ranking organization method (PROMETHEE) under the probabilistic linguistic environment. The probabilistic linguistic evaluations are firstly normalized and transformed to the benefit types. Then, the preference degrees of a subject over other subjects from the same side are obtained by using six types of preference function. Afterwards, groups of preference degrees of a subject are aggregated to the preference indexes by considering the weights of criteria. Hereafter, the preference degrees of a subject over other subjects from the same side are aggregated to the outgoing flow, while the preference degrees of other subjects from the same side over this subject are aggregated to the incoming flow. Furthermore, the net-flows, which is recognized as the satisfaction degrees are calculated by using outgoing flows to minus incoming flows. On the basis of this, the multi-objectives TSMDM model is built by considering the matching aspirations. A model with respect to the matching aspirations is built and solved by using the Lagrange function. The multi-objectives TSMDM model is further transformed to the single-objective model, the solution of which is the matching scheme. A matching problem related to the intelligent technology intermediary is solved to verify the effectiveness and the feasibility of the proposed approach.

A two-sided matching decision-making approach based on regret theory under intuitionistic fuzzy environment

2021 ◽  
pp. 1-18
Author(s):  
Xiang Jia ◽  
Xinfan Wang ◽  
Yuanfang Zhu ◽  
Lang Zhou ◽  
Huan Zhou
Keyword(s):  
Decision Making ◽  
Hamming Distance ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Sets ◽  
Regret Theory ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Objective Model ◽  
Single Objective

This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach.

scholarly journals Probability and loss: two sides of the risk assessment coin

2011 ◽  
Vol 35 (11) ◽  
pp. 413-418 ◽  
Author(s):  
Matthew M. Large ◽  
Olav B. Nielssen
Keyword(s):  
Mental Health ◽  
Risk Assessment ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
The Other ◽  
Current Form ◽  
Mental Health Settings ◽  
Future Harm ◽  
Two Sides

SummaryRisk assessment has been widely adopted in mental health settings in the hope of preventing harms such as violence to others and suicide. However, risk assessment in its current form is mainly concerned with the probability of adverse events, and does not address the other component of risk – the extent of the resulting loss. Although assessments of the probability of future harm based on actuarial instruments are generally more accurate than the categorisations made by clinicians, actuarial instruments are of little assistance in clinical decision-making because there is no instrument that can estimate the probability of all the harms associated with mental illness, or estimate the extent of the resulting losses. The inability of instruments to distinguish between the risk of common but less serious harms and comparatively rare catastrophic events is a particular limitation of the value of risk categorisations. We should admit that our ability to assess risk is severely limited, and make clinical decisions in a similar way to those in other areas of medicine – by informed consideration of the potential consequences of treatment and non-treatment.

scholarly journals BİST’DE İŞLEM GÖREN KÂĞIT VE KÂĞIT ÜRÜNLERİ BASIM VE YAYIN İŞLETMELERİNİN TOPSİS, PROMETHEE VE COPRAS YÖNTEMLERİYLE FİNANSAL PERFORMANSLARININ BELİRLENMESİ

2018 ◽  
Vol 6 (3) ◽  
Author(s):  
Fatma AKYÜZ ◽  
Tolga YEŞİL ◽  
İsmail KARA ◽  
Gürsel ERSOY
Keyword(s):  
Decision Making ◽  
Financial Statements ◽  
Assessment Methods ◽  
Production Costs ◽  
Financial Ratios ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Public Disclosure ◽  
The Public ◽  
Period Performance

Paper and Paper Products in the printing and publishing sector, production costs have increased due to the recent dependence on imports. At this point, Paper and Paper Products Printing and Publishing sector has been preferred and the leading companies in the sector have been tried to be determined by multi-criteria decision making methods. In this study, the financial performances of the paper and paper products printing and publishing sector traded in Borsa Istanbul between the years of 2012-2017, which is one of the multi criteria decision making methods, are the most important decision making methods, PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation and COPRAS (Complex Proportional Assessment) methods. The research sample consisted of 14 companies listed in the BIST. Firstly, the financial ratios used in multi-criteria decision making methods were explained and then the application steps of TOPSİS, PROMETHEE and COPRAS methods were included. During the calculation of financial ratios, the financial statements of the related companies between the years 2012-2017 were used in the light of the data obtained from the Public Disclosure Platform. As a result of the research, the 6-period performance of the companies have rewieved, between the years 2012-2017 was evaluated with 10 financial ratios and the results were compared.

Selection of lean manufacturing systems using the PROMETHEE

2008 ◽  
Vol 3 (1) ◽  
pp. 40-70 ◽  
Author(s):  
G. Anand ◽  
Rambabu Kodali
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Strategic Decision ◽  
Computer Integrated Manufacturing ◽  
Preference Ranking ◽  
Manufacturing Strategy ◽  
Manufacturing Companies ◽  
Content Type

PurposeIn recent years, many manufacturing companies are attempting to implement lean manufacturing systems (LMS) as an effective manufacturing strategy to survive in a highly competitive market. Such a process of selecting a suitable manufacturing system is highly complex and strategic in nature. The paper aims to how companies make a strategic decision of selecting LMS as part of their manufacturing strategy, and on what basis such strategic decisions are made by the managers.Design/methodology/approachA case study of a small‐ and medium‐sized enterprise is presented, in which the managers are contemplating on implementing either computer integrated manufacturing systems (CIMS) or LMS. To supplement the decision‐making process, a multi‐criteria decision making (MCDM) model, namely, the preference ranking organisation method for enrichment evaluations (PROMETHEE) is used to analyse how it will impact the stakeholders of the organisation, and the benefits gained.FindingsAn extensive analysis of PROMETHEE model revealed that LMS was the best for the given circumstances of the case.Research limitations/implicationsThe same problem can be extended by incorporating the constraints (such as financial, technical, social) of the organisation by utilising an extended version of PROMETHEE called the PROMETHEE V. Since, a single case study approach has been utilised, the findings cannot be generalized for any other industry.Practical limitations/implicationsThe methodology of PROMETHEE and its algorithm has been demonstrated in a detailed way and it is believed that it will be useful for managers to apply such MCDM tools to supplement their decision‐making efforts.Originality/valueAccording to the authors’ knowledge there is no paper in the literature, which discusses the application of PROMETHEE in making a strategic decision of implementing LMS as a part of an organisation's manufacturing strategy.

A New Algorithm for Subset Matching Problem Based on Set-String Transformation

2009 ◽  
pp. 607-615
Author(s):  
Yangjun Chen
Keyword(s):  
Programming Languages ◽  
Linear Time ◽  
String Matching ◽  
Special Problem ◽  
Computer Engineering ◽  
Data Types ◽  
Matching Problem ◽  
Matching Problems ◽  
Abstract Data ◽  
Geometric Pattern Matching

In computer engineering, a number of programming tasks involve a special problem, the so-called tree matching problem (Cole & Hariharan, 1997), as a crucial step, such as the design of interpreters for nonprocedural programming languages, automatic implementation of abstract data types, code optimization in compilers, symbolic computation, context searching in structure editors and automatic theorem proving. Recently, it has been shown that this problem can be transformed in linear time to another problem, the so called subset matching problem (Cole & Hariharan, 2002, 2003), which is to find all occurrences of a pattern string p of length m in a text string t of length n, where each pattern and text position is a set of characters drawn from some alphabet S. The pattern is said to occur at text position i if the set p[j] is a subset of the set t[i + j - 1], for all j (1 = j = m). This is a generalization of the ordinary string matching and is of interest since an efficient algorithm for this problem implies an efficient solution to the tree matching problem. In addition, as shown in (Indyk, 1997), this problem can also be used to solve general string matching and counting matching (Muthukrishan, 1997; Muthukrishan & Palem, 1994), and enables us to design efficient algorithms for several geometric pattern matching problems. In this article, we propose a new algorithm on this issue, which needs only O(n + m) time in the case that the size of S is small and O(n + m·n0.5) time on average in general cases.

scholarly journals The Bayesian Prophet: A Low-Regret Framework for Online Decision Making

2020 ◽  
Author(s):  
Alberto Vera ◽  
Siddhartha Banerjee
Keyword(s):  
Decision Making ◽  
Big Data Analytics ◽  
General Technique ◽  
Matching Problems ◽  
Online Matching ◽  
Additive Loss ◽  
Online Decision Making ◽  
Resource Levels ◽  
Greedy Policy ◽  
New Framework

We develop a new framework for designing online policies given access to an oracle providing statistical information about an off-line benchmark. Having access to such prediction oracles enables simple and natural Bayesian selection policies and raises the question as to how these policies perform in different settings. Our work makes two important contributions toward this question: First, we develop a general technique we call compensated coupling, which can be used to derive bounds on the expected regret (i.e., additive loss with respect to a benchmark) for any online policy and off-line benchmark. Second, using this technique, we show that a natural greedy policy, which we call the Bayes selector, has constant expected regret (i.e., independent of the number of arrivals and resource levels) for a large class of problems we refer to as “online allocation with finite types,” which includes widely studied online packing and online matching problems. Our results generalize and simplify several existing results for online packing and online matching and suggest a promising pathway for obtaining oracle-driven policies for other online decision-making settings. This paper was accepted by George Shanthikumar, big data analytics.

Evaluation of energy sources based on sustainability factors using integrated fuzzy MCDM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santosh K. Saraswat ◽  
Abhijeet K. Digalwar
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Economic Benefits ◽  
Decision Makers ◽  
Preference Ranking ◽  
Energy Sources ◽  
Content Type ◽  
Weighted Sum Method ◽  
Weight Calculation ◽  
Social Environmental

Purpose The purpose of this paper is to develop an integrated fuzzy multi-criteria decision-making (MCDM) model for evaluation of the energy alternates in India based on their sustainability. Design/methodology/approach A fuzzy analytical hierarchy process approach is used for the weight calculation of the criteria and the fuzzy technique for order preference by similarity to the ideal solution is used for ranking of the energy alternates. Seven energy sources – thermal, gas power, nuclear, solar, wind, biomass and hydro energy are considered for the assessment purpose on the basis of sustainability criteria, namely, economic, technical, social, environmental, political and flexible. Findings The result of the analysis shows that economics is the highest weight criterion, followed by environmental and technical criteria. Solar energy was chosen as the most sustainable energy alternate in India, followed by wind and hydro energy. Research limitations/implications Few other MCDM techniques such as VIseKriterijumska Optimizacija I Kompromisno Resenje (multi-criteria optimization and compromise solution), weighted sum method and preference ranking organization method for enrichment evaluations – II can also be explored for the sustainability ranking of the energy alternates. However, the present model has also provided a good result. Practical implications The present research work will help the decision-makers and organizations in the evaluation and prioritizing the various energy sources on the scale of sustainability. Social implications Research finding provides guidance to government and decision-makers regarding the development of social conditions through energy security, job creation and economic benefits. Originality/value Research work can be act as a supplement for the investors and decision-makers specifically in prioritizing the investment perspective and to support other multi-perspective decision-making problems.

scholarly journals Habits as action sequences: hierarchical action control and changes in outcome value

2014 ◽  
Vol 369 (1655) ◽  
pp. 20130482 ◽  
Author(s):  
Amir Dezfouli ◽  
Nura W. Lingawi ◽  
Bernard W. Balleine
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Neural Structure ◽  
Action Sequence ◽  
Action Sequences ◽  
Directed Action ◽  
Sequence Boundaries ◽  
High Level ◽  
Step Over ◽  
Two Sides

Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure.

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