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Heuristic strategies for solving the combinatorial optimization problem in real-world credit risk assessment

Yongfeng Gu, Hao Ding, Kecai Gu, Runsheng Gan, Xiaoguang Huang, Yanming Fang, Zhigang Hua, Hua Wu, Jifeng Xuan, Jun Zhou
2022 Proceedings of the Genetic and Evolutionary Computation Conference Companion  
The rule selection problem in credit risk assessment is considered as a combinatorial optimization problem: the goal is to find a subset of rules that maximize the coverage of risky users under given constraints  ...  Experiments on real-world datasets show that the proposed heuristics based on SA, BS, and RIRO can detect the most high-risk users in different datasets.  ...  ACKNOWLEDGMENTS This work is partly supported by the Ant Research Program and the National Natural Science Foundation of China (Grant Nos. 61872273 and 62141221).  ... 
doi:10.1145/3520304.3528924 fatcat:shmop2k5pvbh7nwayehh6w7u24

A Survey on Financial Applications of Metaheuristics

Amparo Soler-Dominguez, Angel A. Juan, Renatas Kizys
2017 ACM Computing Surveys  
to solve rich and reallife combinatorial optimization problems that arise in a number of financial and banking activities.  ...  The paper also discusses some open opportunities for researchers in the field, and forecast the evolution of metaheuristics to include real-life uncertainty conditions into the optimization problems being  ...  Credit Risk Assessment Problem Credit risk is a well-recognized topic in the banking industry. However, the Credit Risk Assessment Problem (CRAP) has gained popularity during the last years.  ... 
doi:10.1145/3054133 fatcat:hr4fggpodnbzjdk3fkg6thxjma

Hybrid Techniques of Combinatorial Optimization with Application to Retail Credit Risk Assessment

Stjepan Oreski
2014 Artificial Intelligence and Applications  
an example of the hybrid technique for feature selection and classification in credit risk assessment.  ...  According to the presented relations among the techniques of combinatorial optimization, the strategies of combining them and the concepts for solving combinatorial optimization problems, this paper presents  ...  The main motivation for the research in this field was provided by thousands of phenomena in the real world that can be formulated, on an abstract level, as combinatorial optimization problems.  ... 
doi:10.15764/aia.2014.01002 fatcat:jeqgqdkoxnh2za66qwhofqbkoq

On the Use of Biased-Randomized Algorithms for Solving Non-Smooth Optimization Problems

Angel Alejandro Juan, Canan Gunes Corlu, Rafael David Tordecilla, Rocio de la Torre, Albert Ferrer
2019 Algorithms  
Despite its many practical applications, non-smooth optimization problems are quite challenging, especially when the underlying optimization problem is NP-hard in nature.  ...  Soft constraints are quite common in real-life applications.  ...  Sona Taheri for inviting us to participate in this special issue in honor of Prof. Dr. Adil M. Bagirov. Conflicts of Interest: The authors declare no conflict of interest. Algorithms 2020, 13, 8  ... 
doi:10.3390/a13010008 fatcat:544u6u63lzeo7lh2dp7evfbwua

Metaheuristics for Rich Portfolio Optimisation and Risk Management: Current State and Future Trends

Jana Doering, Renatas Kizys, Angel A. Juan, Àngels Fitó, Onur Polat
2019 Operations Research Perspectives  
The paper contributes to the existing literature in three ways. Firstly, it reviews the literature on metaheuristic optimisation applications for portfolio and risk management in a systematic way.  ...  This paper reviews the scientific literature on the use of metaheuristics for solving NP-hard versions of these optimisation problems and illustrates their capacity to provide high-quality solutions under  ...  Acknowledgement This work has been partially supported with a doctoral grant from the Universitat Oberta de Catalunya and the Erasmus+ program (2018-1-ES01-KA103-049767).  ... 
doi:10.1016/j.orp.2019.100121 fatcat:ncxpgmkqczdgfl34albgx7z32m

An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications

Bestoun S. Ahmed, Eduard Enoiu, Wasif Afzal, Kamal Z. Zamli
2020 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems.  ...  We applied Q-EMCQ on 37 real-world industrial programs written in Function Block Diagram (FBD) language, which is used for developing a train control management system at Bombardier Transportation Sweden  ...  Specifically, hyperheuristic represents an approach of using (meta)-heuristics to choose (meta)-heuristics to solve the optimization problem at hand (Burke et al. 2003) .  ... 
doi:10.1007/s00500-020-04769-z fatcat:deaquvgr3bgppmrfzd7cl6eq34

Sensor Placement in Municipal Water Networks

Jonathan W. Berry, Lisa Fleischer, William E. Hart, Cynthia A. Phillips, Jean-Paul Watson
2005 Journal of water resources planning and management  
We can exploit this structure to solve the MIP exactly or to approximately solve the problem with provable quality for large-scale problems.  ...  We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal characteristics of contamination events and  ...  Acknowledgements We thank Phil Meyers at Pacific Northwest National Laboratory for noting that DSP is equivalent to the p-median facility location problem.  ... 
doi:10.1061/(asce)0733-9496(2005)131:3(237) fatcat:rfrvbdtyzzgqbfj5nv5t7a5xea

Human performance and strategies while solving an aircraft routing and sequencing problem: an experimental approach

Elizabeth M. Argyle, Robert J. Houghton, Jason Atkin, Geert De Maere, Terry Moore, Hervé P. Morvan
2018 Cognition, Technology & Work  
Through identifying human behavior during optimization problem solving, the work of tower control can be better understood, which, in turn, provides insights for developing decision support systems for  ...  To address this challenge, thirty novice participants solved a set of vehicle routing problems presented in the format of a game representing the airport ground movement task practiced by runway controllers  ...  distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were  ... 
doi:10.1007/s10111-018-0480-4 fatcat:qyczsak23fcrlh7pb5qgvmut3y

Heuristic analysis of a near optimal approximation algorithm for the determination of investment options

Juan Flores, Javier Ávila, Federico González, Beatriz Flores
2009 Revista de Matemática: Teoría y Aplicaciones  
The problem is how much to invest, for how long, and using which of the investment options in order to get the maximum profit out of it.  ...  We find in this work that with the greedy algorithm we use, in general is not possible to optimize the profit for a given function; nevertheless the algorithm we use can find profits that are very close  ...  Acknowledgment The authors wish to thank Jesús Arellano and Pedro Chávez for their valuable contribution with the Lisp implementation.  ... 
doi:10.15517/rmta.v13i2.273 fatcat:5f5tm6ry3bgihiz33ro7rgnzsi

Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic

Jesica de Armas, Angel A. Juan, Joan M. Marquès, João Pedro Pedroso
2017 Journal of the Operational Research Society  
The uncapacitated facility location problem (UFLP) is a popular combinatorial optimization problem with practical applications in different areas, from logistics to telecommunication networks.  ...  While most of the existing work in the literature focuses on minimizing total cost for the deterministic version of the problem, some degree of uncertainty (e.g., in the customers' demands or in the service  ...  Usually the values that can take the inputs of combinatorial optimization problems are not deterministic in real life. In the case of the UFLP, a variety of sources of uncertainty may appear.  ... 
doi:10.1057/s41274-016-0155-6 fatcat:m7zry4mk2nddhlkkrlfsev5zti

An Overview of the Approaches for Automotive Safety Integrity Levels Allocation

Youcef Gheraibia, Sohag Kabir, Khaoula Djafri, Habiba Krimou
2018 Journal of Failure Analysis and Prevention  
There were many successful attempts to solve this problem using different techniques.  ...  ASILs allocation is a hard problem consists of finding the optimal allocation of safety levels to the system architecture which must guarantee that the highest safety requirements are met while development  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s11668-018-0466-9 fatcat:3buvlles5vafnbmrennjscxjgq

A VNS-EDA Algorithm-Based Feature Selection for Credit Risk Classification

Wei Chen, Zhongfei Li, Jinchao Guo
2020 Mathematical Problems in Engineering  
Many quantitative credit scoring models have been developed for credit risk assessment. Irrelevant and redundant features may deteriorate the performance of credit risk classification.  ...  The proposed technique has been tested on both publicly available credit datasets and a real-world credit dataset in China.  ...  Acknowledgments is work was supported in part by the National Natural Science Foundation of China (no. 71721001) and in part by the Natural Science Research Team of Guangdong Province of China (no. 2014A030312003  ... 
doi:10.1155/2020/4515480 fatcat:rnou2dqnlraqrp3fv3espwd5nu

An Introduction to Evolutionary Computation in Finance

Anthony Brabazon, Michael O¿neill, Ian Dempsey
2008 IEEE Computational Intelligence Magazine  
The world of finance is an exciting and challenging environment. Recent years have seen an explosion in the application of Computational Intelligence methodologies in finance.  ...  In this article we provide an overview of some of these applications concentrating on those employing an evolutionary computation approach.  ...  Disclaimer The opinions and inferences in this article are solely those of the authors and do not necessarily reflect the view and opinion of Pipeline Financial Group or Pipeline Trading Systems, LLC.  ... 
doi:10.1109/mci.2008.929841 fatcat:3fhczjtgbvb4ronbwaw6o3sdwi

Enhancing Greedy Policy Techniques for Complex Cost-Sensitive Problems [chapter]

Camelia Vidrighin, Rodica Potole
2008 Greedy Algorithms  
The main task here comes from the difficulty of finding the right search strategy for the particular problem to solve.  ...  This chapter presents ProICET (Vidrighin et al, 2007), a hybrid system for solving complex cost-sensitive problems.  ...  The aim is to achieve increased performance over existing classification algorithms in complex cost problems, usually encountered when mining real-world data, such as in medical diagnosis or credit assessment  ... 
doi:10.5772/6357 fatcat:kgswd7govncwtcau2gko5l3abi

Natural Computing in Finance – A Review [chapter]

Anthony Brabazon, Jing Dang, Ian Dempsey, Michael O'Neill, David Edelman
2012 Handbook of Natural Computing  
The chapter also identifies open issues and suggests future directions for the application of NC methods in finance.  ...  The field of Natural Computing (NC) has advanced rapidly over the past decade. One significant offshoot of this progress has been the application of NC methods in finance.  ...  Credit Risk Assessment Credit risk is the risk that a counterparty to a deal fails to perform their obligations.  ... 
doi:10.1007/978-3-540-92910-9_51 fatcat:qisqzsmfhfhvtdj45maxepwigy
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