Search results

The purpose of this study is modelling of a problem of policing strategy order using a multicriteria method.

For the construction of the impact matrix strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria PROMETHEE II method was used, which with the help of the Visual PROMETHEE software, emulated the systematised data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision makers.

As a result, this research revealed that radio patrol, when used in a non-randomised manner, is the most effective policing strategy in reducing the 18 criminal demands studied in the perception of decision makers after data emulation with the PROMETHEE II method.

As research implications, it can be inferred that the use of multicriteria methods in the modelling of problems in public security area can contribute to the rationalisation of use of the available means in the fight against crime in large cities. This research showed that it is possible to use customised policing strategies to absolute reality.

The practical impact of this research lies in optimising the resources available to law enforcement agencies in the fight against crime in general.

It can be inferred that by choosing appropriate strategies to combat local crime, there is a direct implication in optimising the resources that the government makes available to police agencies. This optimisation allows pressure reduction under the public budget for more features. The model for choosing more effective strategies contributes to local crimes decrease, increasing the sense of the population security.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices and in their associated use in ordering strategies through a multicriteria method. This study contributed to applied police intelligence.

Because that the crime in a wide way impacts the life of the people in the big metropolis, researchers have treated the question from several angles. The purpose of the paper, under the umbrella of operational research, is to develop a model of the ordering of police strategies, in the fight against crime in general, according to a certain criminal demand.

For the construction of the impact matrix of the strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria ELECTRE IV method was used, which with the help of the J-Electre software emulated the systematized data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision-makers.

As a result, the research revealed that policing strategies directed at solving specific crimes are the most effective in the perception of decision-makers after the emulation of data with the ELECTRE IV method.

As research implications, it can be inferred that the use of multicriteria methods in the modeling of problems in the area of public security can contribute to rationalization of the use of the means available in the fight against crime in large cities. The research showed that it is possible to use customized policing strategies to a certain reality.

The method presented in this research is directly related to the major strategies: problem-oriented policing and hot spot policing. This method allows public safety managers to consider the possibility of combining different law enforcement strategies in each context. In this sense, the use of the multiple-criteria decision analysis (MCDA) (ELECTRE IV) method allows the evaluation of a large set of alternatives according to a set of established criteria, speeding up the process and reducing subjectivity, allowing the manager to analyze several scenarios with greater clarity and impartiality and choosing an alternative that best solves the proposed problem. The expected result is the rationalization of the available means applied in the search for the reduction of crime rates.

The customization of policing strategies, according to criminal demands, implies the efficient way to reduce criminal charges. Reducing criminal rates enables the development of the local economy, tourism and the quality of life of people by exercising their freedom to the full.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices, and in their associated use in ordering strategies through a multicriteria method.

This study aims to focus on the application of a multiple criteria decision analysis (MCDA) method to compare results presented by the Integrated Goals System based on the 12th edition of the Integrated Public Safety Areas (IPSAs) Award, which achieved goals established for Strategic Crime Indicators for the state of Rio de Janeiro, Brazil. The main objective of this research was to limit the compensatory effects of classification criteria on IPSAs that have achieved goals established for crime indicators by applying the MCDA method.

The methodology was based on the application of MCDA. The MCDA method selected and used was ELECTRE III, being implemented by J-Electre software.

Compared to results of the current method, the results of the ELECTRE III method showed a 94.87 per cent change in ranking positions revealed via the SIM method. This finding denotes the elimination of compensatory effects of the criteria. As a consequence, it can be affirmed that the application of resources by IPSA managers to reduce the prevalence of a single strategic crime indicator is no longer a success factor for awarding in the established goal system.

As limitations, it is possible to indicate the time cut used to carry out the research. The research may be extended to other issues of the productivity award.

The methodology applied with the use of ELECTRE III revealed that the government could reduce the cost with the incentive program to reduce criminal indices.

As the MCDA method is based on a binary pairwise comparison system, the methodology imposes a change of attitude on local managers fighting crime to reduce crime indicators and to consequently build a local sense of safety in IPSAs.

This research fills a gap in the literature because there are few studies using the MCDA method in the field of public security. The value of the work lies in the creation of a method that gives the decision-maker, of the law enforcement agency, an alternative to improve the process of rewarding by productividad of the integrated areas of public security.

The insecurity generated, today in various parts of the planet, by the various conflicts that arise in the violence in large cities, has motivated the academy to research the solutions and strategies adopted by local governments in the fight against crime. The volume of data generated by several universities over the past 50 years has increased exponentially. Consequently, researchers struggle to process essential data in today’s competitive world. The aim of this study is to explore and provide an overview of the studies carried out in the field of action to combat crime in different countries.

The Web of Science and Scopus databases were searched for publications from January 1945 to September 3, 2020 on the topic of policing strategies in titles, abstracts and keywords. References were analyzed using the R bibliometrix package, and abstracts were analyzed using latent Dirichlet allocation (LDA) with collapsed Gibbs sampling for topics related to policing and related subjects.

As a result of the research, this paper can assert that in the last 50 years, 3,361 authors have produced 2,085 documents on the theme of policing strategy and related subjects in 58 countries. Scientific production in this area grows at a rate of 5.10 per year. The USA is the leading country in publications with 42.58%, followed by the UK with 8.39% and Canada with 4.07%. As for journals, the highlight is Policing, Policing and Society and Police Quarterly, which account for more than 15.44% of all indexed literature. Regarding the authors, the highlight is Weisburd and Braga. As a result, the LDA grouped the latent words in the articles analyzed by themes studied and presented the list of articles by themes. The thematic map identifies the following themes as basic research subjects: community policing, problem-oriented policing, predictive policing, fear of crime and social control.

As the main implication between the combination of the bibliometric analysis method with the probabilistic topic modelling, is the emergence of a primordial step in the systematic literature review process, as this method allows to explore and group a large volume of data. Another practical implication that is intended is to provide the beginning researcher or any other reader with a panoramic view of the main authors who study the themes that impact police activity in any city in the world, which are the countries and reference centers of the study on the subject and, finally, the evolution of the main themes researched in the police area.

The value of these studies is summarized in the presentation of an overview on the theme in the last 50 years, offering the opportunity for other researchers to use this research as a starting point for other analyses.

The database of the Web of Science (WoS) was searched for publications from January 1945–May 7, 2020 on the topic of domestic violence in titles, abstracts and keywords. The references were analyzed using the R bibliometrix package, and abstracts were analyzed using latent Dirichlet allocation (LDA) with collapsed Gibbs sampling to obtain topics related to domestic violence.

The aim of the study is to explore and provide an overview of research carried out on domestic violence, in its various aspects, over the past fifty years.

As a result of the research, the authors can assert that in the last fifty years, 32,298 authors have produced 19,495 documents on the theme of policing strategy and related subjects in 111 countries. Scientific production in this area grows at a rate of 12.81 per year. The United States of America is the leading country in publications with 48.14%, followed by the United Kingdom with 7.57% and Australia with 6.05%. Regarding universities, the highlight is the University of California with 664 publications, followed by the University of London with 515 and the University of North Carolina with 484. As for journals, the highlight is the Journal of Interpersonal Violence, Journal of Family Violence and Violence Against Women, which account for more than 14.32% of all indexed literature. Regarding the authors, the highlight is Campbell J.C and Feder G. Probabilistic topic modeling revealed that 18% of the topics concentrate 90% of all tokens. Topic 1 accounts for 27.9% of the sample and conducts research related to intimate partner violence.

As a practical implication of using the LDA in the bibliographic review, we infer that its capacity to explore large masses of data allows the researcher to explore an infinitely greater amount than the traditional methods of systematic literature review.

The value of these studies is summarized in the presentation of an overview on the theme in the last fifty years, offering the opportunity for other researchers to use this research as a starting point for other analyses.

The purpose of this paper is to develop a method for the discovery of knowledge in emergency response databases based on police incident reports, generating information that identifies local criminal demands that allow the selection of the appropriate policing strategies portfolio to solve the problem.

The developed model uses a methodology for the discovery of knowledge involving text mining techniques using Latent Dirichlet Allocation (LDA) integrated with the ELECTRE I multicriteria method.

The developed method allowed the identification of the most common criminal demands that occurred from January 1 to December 31, 2016, in the policing areas studied. One of the crimes does not occur homogeneously in a particular locality. In this study, it was initially observed that 40 per cent of the crimes identified in the Integrated Public Safety Area 5, or AISP-5, (historical city center of RJ) had no correlation with AISP-19 (Copacabana - RJ), and 33 per cent of crimes crimes in AISP-19 were not identified in AISP-5. This finding guided the second part of the method that sought to identify which portfolio of policing strategies would be most appropriate for the identified demands. In this sense, using the ELECTRE I method, eight different scenarios were constructed where it can be identified that for each specific criminal demand set there is a set of policing strategies to be applied.

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

The developed methodology contributes in a complementary way to the identification of criminal practices and their characteristics based on reports of police occurrences stored in emergency response databases. The knowledge generated through the identification of criminal demands allows law enforcement decision makers to evaluate and choose among the available policing strategies, which best suit the reality they study, and produce the reduction of criminal indices.

It is possible to infer that by choosing appropriate strategies to combat local crime, the proposed model will increase the population’s sense of safety through an effective reduction in crime.

The originality of the study lies in the integration of text mining techniques, LDA and the ELECTRE I method for detecting crime in a given location based on crime reports stored in emergency response databases, enabling identification and choice, from customized policing strategies to particular criminal demands.

The purpose of this paper is to develop a methodology for knowledge discovery in emergency response service databases based on police occurrence reports, generating information to help law enforcement agencies plan actions to investigate and combat criminal activities.

The developed model employs a methodology for knowledge discovery involving text mining techniques and uses latent Dirichlet allocation (LDA) with collapsed Gibbs sampling to obtain topics related to crime.

The method used in this study enabled identification of the most common crimes that occurred in the period from 1 January to 31 December of 2016. An analysis of the identified topics reaffirmed that crimes do not occur in a linear manner in a given locality. In this study, 40 per cent of the crimes identified in integrated public safety area 5, or AISP 5 (the historic centre of the city of RJ), had no correlation with AISP 19 (Copacabana – RJ), and 33 per cent of the crimes in AISP 19 were not identified in AISP 5.

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

The developed methodology contributes in a complementary manner to the identification of criminal practices and their characteristics based on police occurrence reports stored in emergency response databases. The generated knowledge enables law enforcement experts to assess, reformulate and construct differentiated strategies for combating crimes in a given locality.

The production of knowledge from the emergency service database contributes to the government integrating information with other databases, thus enabling the improvement of strategies to combat local crime. The proposed model contributes to research on big data, on the innovation aspect and on decision support, for it breaks with a paradigm of analysis of criminal information.

The originality of the study lies in the integration of text mining techniques and LDA to detect crimes in a given locality on the basis of the criminal occurrence reports stored in emergency response service databases.

Although the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive priority vector (weights) for a set of criteria, there is a significant drawback in using this technique if the pairwise comparison matrix (PCM) has inconsistent comparisons, in other words, a consistency ratio (CR) above the value of 0.1, the final solution cannot be validated. Many studies have been developed to treat the inconsistency problem, but few of them tried to satisfy different quality measures, which are minimum inconsistency (fMI), the total number of adjusted pairwise comparisons (fNC), original rank preservation (fKT), minimum average weights adjustment (fWA) and finally, minimum L1 matrix norm between the original PCM and the adjusted PCM (fLM).

The approach is defined in four steps: first, the decision-maker should choose which quality measures she/he wishes to use, ranging from one to all quality measures. In the second step, the authors encode the PCM to be used in a many-objective optimization algorithm (MOOA), and each pairwise comparison can be adjusted individually. The authors generate consistent solutions from the obtained Pareto optimal front that carry the desired quality measures in the third step. Lastly, the decision-maker selects the most suitable solution for her/his problem. Remarkably, as the decision-maker can choose one (mono-objective), two (multi-objective), three or more (many-objectives) quality measures, not all MOOAs can handle or perform well in mono- or multi-objective problems. The unified non-sorting algorithm III (U-NSGA III) is the most appropriate MOOA for this type of scenario because it was specially designed to handle mono-, multi- and many-objective problems.

The use of two quality measures should not guarantee that the adjusted PCM is similar to the original PCM; hence, the decision-maker should consider using more quality measures if the objective is to preserve the original PCM characteristics.

For the first time, a many-objective approach reduces the CR to consistent levels with the ability to consider one or more quality measures and allows the decision-maker to adjust each pairwise comparison individually.

This paper aims to present a set of five models for the economic order quantity problem. Four models solve problems for a single product: incremental discounts with or without backorders and all-unit discounts with or without backorders, and the last model solves problems for the multiproduct case.

A basic integer non-linear model with binary variables is presented, and its flexible structure allows for all five models to be utilised with minor modifications for adaptation to individual situations. The multiproduct model takes into consideration the work of Chopra and Meindl (2012), who studied two types of product aggregations: full and adaptive. To find optimal or near-optimal solutions for the multiproduct case, the authors propose a simulated annealing metaheuristic application. Numerical examples are presented to improve the comprehension of each model, and the authors also present the efficiency of the simulated annealing algorithm through an example that aggregates 50 products, each one with different discount schemes and some allowing backorders.

Our model proved to be efficient at finding optimal or near optimal solutions even when confronted with mathematical complexities such as the allowance of backorders and incremental discounts.

Finally our model can process a mix of products with different discount schemes at the same time, and the simulated annealing metaheuristics could find optimal or near optimal solutions with very few iterations.

This paper presents an algorithm that can elicitate all or any combination of parameters for the ELECTRE II, III or IV, methods. The algorithm takes some steps of a machine learning ensemble technique, the random forest, and for that, the authors named the approach as Ranking Trees Algorithm.

First, for a given method, the authors generate a set of ELECTRE models, where each model solves a random sample of criteria and actions (alternatives). Second, for each generated model, all actions are projected in a 1D space; in general, the best actions have higher values in a 1D space than the worst ones; therefore, they can be used to guide the genetic algorithm in the final step, the optimization phase. Finally, in the optimization phase, each model has its parameters optimized.

The results can be used in two different ways; the authors can merge all models, to find the elicitated parameters in this way, or the authors can ensemble the models, and the median of all ranks represents the final rank. The numerical examples achieved a Kendall Tau correlation rank over 0.85, and these results could perform as well as the results obtained by a group of specialists.

For the first time, the elicitation of ELECTRE parameters is made by an ensemble technique composed of a set of uncorrelated multicriteria models that can generate robust solutions.