Reducing the Computational Time for the Kemeny Method by Exploiting Condorcet Properties

Preference aggregation and in particular ranking aggregation are mainly studied by the field of social choice theory but extensively applied in a variety of contexts. Among the most prominent methods for ranking aggregation, the Kemeny method has been proved to be the only one that satisfies some desirable properties such as neutrality, consistency and the Condorcet condition at the same time. Unfortunately, the problem of finding a Kemeny ranking is NP-hard, which prevents practitioners from using it in real-life problems. The state of the art of exact algorithms for the computation of the Kemeny ranking experienced a major boost last year with the presentation of an algorithm that provides searching time guarantee up to 13 alternatives. In this work, we propose an enhanced version of this algorithm based on pruning the search space when some Condorcet properties hold. This enhanced version greatly improves the performance in terms of runtime consumption.

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A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-011-0058-2 ◽

2011 ◽

Vol 21 (4) ◽

pp. 733-744 ◽

Cited By ~ 1

Author(s):

Marlene Arangú ◽

Miguel Salido

Keyword(s):

Constraint Satisfaction ◽

Constraint Programming ◽

Real Life ◽

Search Space ◽

Constraint Satisfaction Problems ◽

Fine Grained ◽

Arc Consistency ◽

Life Problems ◽

Programming Techniques ◽

Np Complete

A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems Constraint programming is a powerful software technology for solving numerous real-life problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NP-complete so filtering techniques to reduce the search space are still necessary. Arc-consistency algorithms are widely used to prune the search space. The concept of arc-consistency is bidirectional, i.e., it must be ensured in both directions of the constraint (direct and inverse constraints). Two of the most well-known and frequently used arc-consistency algorithms for filtering CSPs are AC3 and AC4. These algorithms repeatedly carry out revisions and require support checks for identifying and deleting all unsupported values from the domains. Nevertheless, many revisions are ineffective, i.e., they cannot delete any value and consume a lot of checks and time. In this paper, we present AC4-OP, an optimized version of AC4 that manages the binary and non-normalized constraints in only one direction, storing the inverse founded supports for their later evaluation. Thus, it reduces the propagation phase avoiding unnecessary or ineffective checking. The use of AC4-OP reduces the number of constraint checks by 50% while pruning the same search space as AC4. The evaluation section shows the improvement of AC4-OP over AC4, AC6 and AC7 in random and non-normalized instances.

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SOSerbia: Android-Based Software Platform for Sending Emergency Messages

Complexity ◽

10.1155/2018/8283919 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9

Author(s):

Mihailo Jovanovic ◽

Ivan Babic ◽

Milan Cabarkapa ◽

Jelena Misic ◽

Sasa Mijalkovic ◽

...

Keyword(s):

Emergency Response ◽

State Of The Art ◽

Complete Solution ◽

Real Life ◽

Android Application ◽

Unique Combination ◽

Background Process ◽

Life Problems ◽

The Republic ◽

National Police

This paper presents Android-based SOS platform named SOSerbia for sending emergency messages by citizens in Serbia. The heart of the platform is SOS client Android application which is an easy and simple solution for sending SOS messages with unique combination of volume buttons. The proposed platform solves a lot of safety, security, and emergency problems for people who can be in dangerous situations. After a person presses a correct combination of buttons, a message with his or her location is sent to the operating center of the Serbian Police. The platform merges several appropriately combined advanced Android technologies into one complete solution. The proposed solution also uses the Google location API for getting user’s location and Media Player broadcast receiver for reading pressed buttons for volume. This logic can be also customized for any other mobile operating system. In other words, the proposed architecture can be also implemented in iOS or Windows OS. It should be noted that the proposed architecture is optimized for different mobile devices. It is also implemented with simple widget and background process based on location. The proposed platform is experimentally demonstrated as a part of emergency response center at the Ministry of Interior of the Republic of Serbia. This platform overcomes real-life problems that other state-of-the-art solutions introduce and can be applied and integrated easily in any national police and e-government systems.

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Social Choice Theory and Legislative Institutions

10.1093/acrefore/9780190228637.013.1 ◽

2016 ◽

Author(s):

Nicholas R. Miller

Keyword(s):

Social Choice ◽

Choice Theory ◽

Social Choice Theory ◽

Decision Rules ◽

Spatial Models ◽

Preference Aggregation ◽

Simple Majority ◽

Forthcoming Article ◽

Aggregation Functions ◽

Legislative Institutions

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Politics. Please check back later for the full article.Narrowly understood, social choice theory is a specialized branch of applied logic and mathematics that analyzes abstract objects called preference aggregation functions, social welfare functions, and social choice functions. But more broadly, social choice theory identifies, analyzes, and evaluates rules that may be used to make collective decisions. So understood, social choice is a subfield of the social sciences that examines what may be called “voting rules” of various sorts. While social choice theory typically assumes a finite set of alternatives over which voter preferences are unrestricted, the spatial model of social choice assumes that policy alternatives can be represented by points in a space of one or more dimensions, and that voters have preferences that are plausibly shaped by this spatial structure.Social choice theory has considerable relevance for the study of legislative (as well as electoral) institutions. The concepts and tools of social choice theory make possible formal descriptions of legislative institutions such as bicameralism, parliamentary voting procedures, effects of decision rules (e.g., supramajority vs. simple majority rule and executive veto rules), sincere vs. strategic voting by legislators, agenda control, and other parliamentary maneuvers. Spatial models of social choice further enrich this analysis and raise additional questions regarding policy stability and change. Spatial models are used increasingly to guide empirical research on legislative institutions and processes.

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Artificial Bee Colony Algorithm with Directed Scout

10.21203/rs.3.rs-279600/v1 ◽

2021 ◽

Author(s):

Radhwan A.A. Saleh ◽

Rüştü Akay

Keyword(s):

Design Problem ◽

Artificial Bee Colony Algorithm ◽

Artificial Bee Colony ◽

Optimization Problems ◽

Real Life ◽

Search Space ◽

Bee Colony ◽

Life Problems ◽

Tension And Compression ◽

Teaching Learning

Abstract As a relatively new model, the Artificial Bee Colony Algorithm (ABC) has shown impressive success in solving optimization problems. Nevertheless, its efficiency is still not satisfactory for some complex optimization problems. This paper has modified ABC and its other recent variants to improve its performance by modify the scout phase. This modification enhances its exploitation ability by intensifying the regions in the search space, which probably includes reasonable solutions. The experiments were performed on the CEC2014 benchmark suite, CEC2015 benchmark functions, and three real-life problems: pressure vessel design problem, tension and compression spring design problem, and Frequency-Modulated (FM) problem. And the proposed modification was applied to basic ABC, Gbest-Guided ABC, Depth First Search ABC, and Teaching Learning Based ABC, and they were compared with their modified counterparts. The results have shown that our modification can successfully increase the performance of the original versions. Moreover, the proposed modified algorithm was compared with the state-of-the-art optimization algorithms, and it produced competitive results.

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A New Upper Bound Based on Vertex Partitioning for the Maximum K-plex Problem

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2021/233 ◽

2021 ◽

Author(s):

Hua Jiang ◽

Dongming Zhu ◽

Zhichao Xie ◽

Shaowen Yao ◽

Zhang-Hua Fu

Keyword(s):

Branch And Bound ◽

Upper Bound ◽

Undirected Graph ◽

State Of The Art ◽

Search Space ◽

Exact Algorithms ◽

Induced Subgraph ◽

Massive Graphs ◽

Vertex Set ◽

Number Of Branches

Given an undirected graph, the Maximum k-plex Problem (MKP) is to find a largest induced subgraph in which each vertex has at most k−1 non-adjacent vertices. The problem arises in social network analysis and has found applications in many important areas employing graph-based data mining. Existing exact algorithms usually implement a branch-and-bound approach that requires a tight upper bound to reduce the search space. In this paper, we propose a new upper bound for MKP, which is a partitioning of the candidate vertex set with respect to the constructing solution. We implement a new branch-and-bound algorithm that employs the upper bound to reduce the number of branches. Experimental results show that the upper bound is very effective in reducing the search space. The new algorithm outperforms the state-of-the-art algorithms significantly on real-world massive graphs, DIMACS graphs and random graphs.

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”Hvorfor så meget stabilitet”? Stabiliserende elementer i det danske politiske system

Politik ◽

10.7146/politik.v15i2.27513 ◽

2012 ◽

Vol 15 (2) ◽

Author(s):

Malthe Munkøe

Keyword(s):

Social Choice ◽

Political System ◽

Choice Theory ◽

Social Choice Theory ◽

Point Of View ◽

Preference Aggregation ◽

The Political ◽

Empirical Question ◽

Strategic Manipulation ◽

Collective Preference

Social choice research has shown that collective preference aggregation mechanisms under some conditions will produce arbitrary results, and are prone to endless cycles or strategic manipulation. is prompted Tul- lock (1981) to ask the question “Why so much stability”? at is to say, what explains the discrepancy between these results which implicates that politics is chaotic and random, and general understanding of how politics works in practice. e literature has identi ed a number of mechanisms, including “structure-inducing” in- stitutions that have a stabilizing e ect on the political system. As such it is ultimately an empirical question to what extent a political system is stable or not, and what institutions, norms and arrangements engender stability. is article considers the Danish political system from the point of view of social choice theory and discusses which institutions and arrangements work to stabilize it.

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A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems

Journal of Modern Manufacturing Systems and Technology ◽

10.15282/jmmst.v1i1.195 ◽

2018 ◽

Vol 1 (1) ◽

pp. 15-26

Author(s):

D B Fatemeh ◽

C K Loo ◽

G Kanagaraj ◽

S G Ponnambalam

Keyword(s):

Penalty Method ◽

Optimization Problems ◽

Real Life ◽

Search Space ◽

Computational Time ◽

Shuffled Complex Evolution ◽

Centroidal Voronoi Tessellations ◽

Adaptive Penalty ◽

Adaptive Penalty Method

Most real-life optimization problems involve constraints which require a specialized mechanism to deal with them. The presence of constraints imposes additional challenges to the researchers motivated towards the development of new algorithm with efficient constraint handling mechanism. This paper attempts the suitability of newly developed hybrid algorithm, Shuffled Complex Evolution with Quantum Particle Swarm Optimization abbreviated as SP-QPSO, extended specifically designed for solving constrained optimization problems. The incorporation of adaptive penalty method guides the solutions to the feasible regions of the search space by computing the violation of each one. Further, the algorithm’s performance is improved by Centroidal Voronoi Tessellations method of point initialization promise to visit the entire search space. The effectiveness and the performance of SP-QPSO are examined by solving a broad set of ten benchmark functions and four engineering case study problems taken from the literature. The experimental results show that the hybrid version of SP-QPSO algorithm is not only overcome the shortcomings of the original algorithms but also outperformed most state-of-the-art algorithms, in terms of searching efficiency and computational time.

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Rousseau's Anti–Agenda-Setting Agenda and Contemporary Democratic Theory

American Political Science Review ◽

10.1017/s0003055405051543 ◽

2005 ◽

Vol 99 (1) ◽

pp. 137-144 ◽

Cited By ~ 7

Author(s):

JOHN T. SCOTT

Keyword(s):

Political Theory ◽

Agenda Setting ◽

Majority Rule ◽

Choice Theory ◽

Separation Of Powers ◽

Social Choice Theory ◽

Preference Aggregation ◽

Democratic Principle ◽

Legislative Initiative ◽

Democratic Principles

In his recent article, “Rousseau on Agenda-Setting and Majority Rule” (2003), Ethan Putterman examines how the democratic principle of popular majority rule might be reconciled with agenda-setting by legislative experts through an analysis of Rousseau's political theory. He argues that Rousseau accomplishes this reconciliation through a novel separation of powers between the legislative and the executive powers where the sovereign people delegates the exclusive power to initiate laws to the executive. Putterman thereby identifies as a solution to the problem of democratic self-legislation what Rousseau sees as the most important danger to it. At issue is not merely the correct interpretation of Rousseau's theory, for Putterman's argument raises far-reaching questions concerning the compatibility of democratic principles and institutions. After demonstrating that Putterman is incorrect that the sovereign people in Rousseau's state delegate the power of legislative initiative, I examine how Rousseau anticipates and addresses a related question central to contemporary democratic and social choice theory: the problem of preference aggregation through voting in the absence of agenda-setting institutions.

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AGGREGATING MORAL PREFERENCES

Economics and Philosophy ◽

10.1017/s0266267115000486 ◽

2016 ◽

Vol 32 (2) ◽

pp. 283-321 ◽

Cited By ~ 3

Author(s):

Matthew D. Adler

Keyword(s):

Social Choice ◽

Choice Theory ◽

Social Choice Theory ◽

Preference Aggregation ◽

Moral Goodness ◽

Aggregation Problem ◽

Moral Facts

Abstract:Preference-aggregation problems arise in various contexts. One such context, little explored by social choice theorists, is metaethical. ‘Ideal-advisor’ accounts, which have played a major role in metaethics, propose that moral facts are constituted by the idealized preferences of a community of advisors. Such accounts give rise to a preference-aggregation problem: namely, aggregating the advisors’ moral preferences. Do we have reason to believe that the advisors, albeit idealized, can still diverge in their rankings of a given set of alternatives? If so, what are the moral facts (in particular, the comparative moral goodness of the alternatives) when the advisors do diverge? These questions are investigated here using the tools of Arrovian social choice theory.

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Automatic Feature Selection for Stenosis Detection in X-ray Coronary Angiograms

Mathematics ◽

10.3390/math9192471 ◽

2021 ◽

Vol 9 (19) ◽

pp. 2471

Author(s):

Miguel-Angel Gil-Rios ◽

Igor V. Guryev ◽

Ivan Cruz-Aceves ◽

Juan Gabriel Avina-Cervantes ◽

Martha Alicia Hernandez-Gonzalez ◽

...

Keyword(s):

Feature Selection ◽

Learning Strategies ◽

High Performance ◽

State Of The Art ◽

Search Space ◽

Jaccard Index ◽

Computational Time ◽

X Ray ◽

Coronary Angiograms ◽

Automatic Feature Selection

The automatic detection of coronary stenosis is a very important task in computer aided diagnosis systems in the cardiology area. The main contribution of this paper is the identification of a suitable subset of 20 features that allows for the classification of stenosis cases in X-ray coronary images with a high performance overcoming different state-of-the-art classification techniques including deep learning strategies. The automatic feature selection stage was driven by the Univariate Marginal Distribution Algorithm and carried out by statistical comparison between five metaheuristics in order to explore the search space, which is O(249) computational complexity. Moreover, the proposed method is compared with six state-of-the-art classification methods, probing its effectiveness in terms of the Accuracy and Jaccard Index evaluation metrics. All the experiments were performed using two X-ray image databases of coronary angiograms. The first database contains 500 instances and the second one 250 images. In the experimental results, the proposed method achieved an Accuracy rate of 0.89 and 0.88 and Jaccard Index of 0.80 and 0.79, respectively. Finally, the average computational time of the proposed method to classify stenosis cases was ≈0.02 s, which made it highly suitable to be used in clinical practice.

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