Category Archives: Business Analytics

Distressed Chinese firm prediction with discretized data

Jun Huang, Jun Huang, Haibo Wang, Haibo Wang, Gary Kochenberger, Gary Kochenberger
Management Decision,Vol. 55, Issue 5, Pages: 786-807.

Purpose The authors develop a framework to build an early warning mechanism in detecting financial deterioration of Chinese companies. Many studies in the financial distress and bankruptcy prediction literature rarely do they examine the impact of pre-processing financial indicators on the prediction performance. The purpose of this paper is to address this shortcoming. Design/methodology/approach The proposed framework is evaluated by using both original and discretized data, and a least absolute shrinkage and selection …
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A Selective Linearization Method For Multiblock Convex Optimization

Yu Du, Xiaodong Lin, Andrzej Ruszczyski
SIAM Journal on Optimization,Vol. 27, Issue 2, Pages: 1102-1117.

We consider the problem of minimizing a sum of several convex nonsmooth functions. We introduce a new algorithm called the selective linearization method, which iteratively linearizes all but one of the functions and employs simple proximal steps. The algorithm is a form of multiple operator splitting in which the order of processing partial functions is not fixed, but rather determined in the course of calculations. Global convergence is proved and estimates of the convergence rate are derived. Specifically, the number of iterations …
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Rate of Convergence of the Bundle Method

Yu Du, Andrzej Ruszczyski
Journal of Optimization Theory and Applications,Vol. 173, Issue 3, Pages: 908-922.

The number of iterations needed by the bundle method for nonsmooth optimization to achieve a specified solution accuracy can be bounded by the product of the inverse of the accuracy and its logarithm, if the function is strongly convex. The result is true for the versions of the method with multiple cuts and with cut aggregation.
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A Technical/Strategic Paradigm for Online Executive Education

Marlene A Smith, Susan M Keaveney
Decision Sciences Journal of Innovative Education,Vol. 15, Issue 1, Pages: 82-100.

This article discusses the development and delivery of online courses for the executive education audience. The goal is to introduce a new framework, the technical/strategic paradigm, that will help educators to identify the pedagogical needs of disparate executive groups and adjust their online course development plans accordingly. We describe how four key elements of online courses (course structure, content-based learning materials, assignments, and learning assessment) should be fashioned in a way …
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Preface to the 2nd Special Issue on metaheuristics in network optimization

Gary Kochenberger, Fred Glover
Networks,Vol. 68, Issue 1, Pages: 3-3.

If you can’t find a tool you’re looking for, please click the link at the top of the page to” Go to old article view”. Alternatively, view our Knowledge Base articles for additional help. Your feedback is important to us, so please let us know if you have comments or ideas for improvement.
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Probabilistic multistart with path relinking for solving the unconstrained binary quadratic problem

Mark Lewis, Gary Kochenberger
International Journal of Operational Research,Vol. 26, Issue 1, Pages: 13-33.

The unconstrained binary quadratic problem (UBQP) has been shown to be an excellent framework from which to solve many types of problems, both constrained and unconstrained. In this paper we investigate a solution technique for UBQP that is based on perturbing a solution by drawing from the distribution of variables’ estimated effect as determined via an unbiased design of experiments (DOE) sampling of the solution space. Solution perturbation is followed by a steepest ascent local search with path relinking. A …
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Output from Statistical Predictive Models as Input to eLearning Dashboards

Marlene A Smith
Future Internet,Vol. 7, Issue 2, Pages: 170-183.

We describe how statistical predictive models might play an expanded role in educational analytics by giving students automated, real-time information about what their current performance means for eventual success in eLearning environments. We discuss how an online messaging system might tailor information to individual students using predictive analytics. The proposed system would be data-driven and quantitative; eg, a message might furnish the probability that a student will successfully complete the …
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Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs

Fred Glover, Tao Ye, Abraham P. Punnen, Gary Kochenberger
European Journal of Operational Research, Volume 241, Issue 3, 16 March 2015, Pages 697–707

The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem. The model has a variety of real life applications; however, empirical studies of the model are not available in the literature, except in a few isolated instances. In this paper, we develop efficient heuristic algorithms based on tabu search, very large scale neighborhood (VLSN) search, and a hybrid algorithm that integrates the two. The computational study establishes that effective integration of simple tabu search with VLSN search results in superior outcomes, and suggests the value of such an integration in other settings. Complexity analysis and implementation details are provided along with conclusions drawn from experimental analysis. In addition, we obtain solutions better than the best previously known for almost all medium and large size benchmark instances.

Exact solutions to generalized vertex covering problems: a comparison of two models

Gary Kochenberger, Mark Lewis, Fred Glover, Haibo Wang
Optimization Letters, In Press

The generalized vertex cover problem (GVCP) was recently introduced in the literature and modeled as a binary linear program. GVCP extends classic vertex cover problems to include both node and edge weights in the objective function. Due to reported difficulties in finding good solutions for even modest sized problems via the use of exact methods (CPLEX), heuristic solutions obtained from a customized genetic algorithm (GA) were reported by Milanovic (Comput Inf 29:1251–1265, 2010). In this paper we consider an alternative model representation for GVCP that translates the constrained linear (binary) form to an unconstrained quadratic binary program and compare the linear and quadratic models via computations carried out by CPLEX’s branch-and-cut algorithms. For problems comparable to those previously studied in the literature, our results indicate that the quadratic model efficiently yields optimal solutions for many large GVCP problems. Moreover, our quadratic model dramatically outperforms the corresponding linear model in terms of time to reach and verify optimality and in terms of the optimality gap for problems where optimality is unattained.

Apology Strategies for Informal Complaints in Service Recovery and CRM Systems

Deborah L. Kellogg and Lawrence F. Cunningham
International Journal of Information Systems and Social Change, Volume 5 Issue 3

This paper reports the results of a quasi-experiment designed to identify linkages between customer attributes and apology types in service recovery in informal resolution settings. Understanding these relationships is critical for enabling more effective and dynamic social relationships between the service provider and the customer/client with the use of technology, namely Customer Relationship Management Systems (CRM). The authors find that simple apologies decrease anger, restore distributive and interactional justice, and increase satisfaction. More importantly, the paper suggests that there are significant nuances in apology types and complex relationships between customer types and effective deployment of the apology in informal resolution settings. Further, the analysis suggests that apologies with explanations are more effective among customers with service experience and that apologies with compensation are most effective for all customers. When apologies are used with successive failures there is some evidence that the apology explanations are not equally effective for all customer types. The paper concludes with a discussion of the linkages between apology, service recovery and CRM systems in informal complaint resolution to improve senior level decision making, employee performance in service recovery, and customer satisfaction in for profit and non-profit organizations.

The unconstrained binary quadratic programming problem: a survey

Gary Kochenberger, Jin-Kao Hao, Fred Glover, Mark Lewis, Zhipeng Lü, Haibo Wang, Yang Wang
Journal of Combinatorial Optimization, July 2014, Volume 28, Issue 1, pp 58-81

In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution techniques for this basic model that encompasses a rich collection of problem types. In this paper we survey the literature on this important model, providing an overview of the applications and solution methods.

Exact Solutions to the Capacitated Clustering Problem: A Comparison of Two Models

Mark Lewis, Haibo Wang, Gary Kochenberger
Annals of Data Science, March 2014, Volume 1, Issue 1, pp 15-23

In this paper, we investigate a natural nonlinear alternative to a standard linear model for CCP and compare the two models on a set of test problems. Our results show that moderate sized instances of CCP can in fact be solved optimally with modern exact methods in modest amounts of time and that the quadratic model generally outperformed its equivalent linear alternative in terms of quickly finding optimal or near optimal solutions.

Solving large scale Max Cut problems via tabu search

Gary A. Kochenberger, Jin-Kao Hao, Zhipeng Lü, Haibo Wang and Fred Glover
Journal of Heuristics, Volume 19, Issue 4, August 2013, pp 565-571

In recent years many algorithms have been proposed in the literature for solving the Max-Cut problem. In this paper we report on the application of a new Tabu Search algorithm to large scale Max-cut test problems. Our method provides best known solutions for many well-known test problems of size up to 10,000 variables, although it is designed for the general unconstrained quadratic binary program (UBQP), and is not specialized in any way for the Max-Cut problem.

Introduction to special xQx issue

Gary Kochenberger, Fred Glover
Journal of Heuristics,Vol. 19, Issue 4, Pages: 525-528.

The Unconstrained Binary Quadratic Programming (UBQP) problem is notable for encompassing a remarkable range of applications in combinatorial optimization. As observed in Kochenberger et al.(2013), classes of problems that can be formally expressed using UBQP formulations include: Quadratic Assignment Problems, Capital Budgeting Problems, Multiple Knapsack Problems, Task Allocation Problems (distributed computer systems), Maximum Diversity Problems, P-Median Problems, Asymmetric Assignment …
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Graph Bisection Modeled As Cardinality Constrained Binary Quadratic Task Allocation

Mark Lewis and Gary Kochenberger
International Journal of Information Technology & Decision Making.
(2013) Vol. 12, Issue 2

In this paper, the cardinality constrained quadratic model for binary quadratic programming is used to model and solve the graph bisection problem as well as its generalization in the form of the task allocation problem with two processors (2-TAP). Balanced graph bisection is an NP-complete problem which partitions a set of nodes in the graph G = (N, E) into two sets with equal cardinality such that a minimal sum of edge weights exists between the nodes in the two separate sets. 2-TAP is graph bisection with the addition of node preference costs in the objective function. We transform the general linear k-TAP model to the cardinality constrained quadratic binary model so that it may be efficiently solved using tabu search with strategic oscillation. On a set of benchmark graph bisections, we improve the best known solution for several problems. Comparison results with the state-of-the-art graph partitioning program METIS, as well as Cplex and Gurobi are presented on a set of randomly generated graphs. This approach is shown to also work well with 2-TAP, comparing favorably to Cplex and Gurobi, providing better solutions in a much shorter time.

Mann–Whitney test with adjustments to pretreatment variables for missing values and observational study

Song Xi Chen, Jing Qin, and Cheng Yong Tang
Journal of the Royal Statistical Society,  Jan. 2013, Vol. 75 Issue 1, pp. 81-102

The conventional Wilcoxon or Mann–Whitney test can be invalid for comparing treatment effects in the presence of missing values or in observational studies. This is because the missingness of the outcomes or the participation in the treatments may depend on certain pretreatment variables.We propose an approach to adjust the Mann–Whitney test by correcting the potential bias via consistently estimating the conditional distributions of the outcomes given the pretreatment variables.We also propose semiparametric extensions of the adjusted Mann-Whitney test which lead to dimension reduction for high dimensional covariates. A novel bootstrap procedure is devised to approximate the null distribution of the test statistics for practical implementations. Results from simulation studies and an economics observational study data analysis are presented to demonstrate the performance of the approach proposed.

Forecasting emergency department arrivals: a tutorial for emergency department directors

Murray J Cote, Marlene A Smith, David R Eitel, Elif Akali
Hospital topics,Vol. 91, Issue 1, Pages: 9-19.

This article is a tutorial for emergency department (ED) medical directors needing to anticipate ED arrivals in support of strategic, tactical, and operational planning and activities. The authors demonstrate our regression-based forecasting models based on data obtained from a large teaching hospital’s ED. The versatility of the regression analysis is shown to readily accommodate a variety of forecasting situations. Trend regression analysis using annual ED arrival data shows the long-term growth. The monthly and daily variation in ED …
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nue Gains from MultiTier Ticket Pricing: Evidence from Pop Music Concerts

E. Woodrow Eckard and Marlene A. Smith
Managerial and Decision Economics, Vol 33, Issue 7-8, Oct 2012, pages 463–473

We provide empirical estimates of the revenue benefits of multi-tier pricing at a major US pop music venue. Our unique sample includes data on the number of tickets sold at every price. Mean revenue gain from multi-tier pricing is estimated to be about $20,000 per show, a 4.2% increase over uniform pricing, although the gains were as high as 21.2% for one performer. We also provide evidence that customer segmentation by income is a likely motive of multi-tier pricing and, for the first time, that the standard assumption of zero marginal cost of additional venue attendees is valid.

Sparse Matrix Graphical Models

Chenlei Leng and Cheng Yong Tang
Journal of the American Statistical Association
. 107 1187-1200.

Matrix-variate observations are frequently encountered in many contemporary statistical problems due to a rising need to organize and analyze data with structured information. In this article, we propose a novel sparse matrix graphical model for these types of statistical problems. By penalizing, respectively, two precision matrices corresponding to the rows and columns, our method yields a sparse matrix graphical model that synthetically characterizes the underlying conditional independence structure. Our model is more parsimonious and is practically more interpretable than the conventional sparse vector-variate graphical models. Asymptotic analysis shows that our penalized likelihood estimates enjoy better convergent rates than that of the vector-variate graphical model. The finite sample performance of the proposed method is illustrated via extensive simulation studies and several real datasets analysis

An efficient empirical likelihood approach for estimating equations with missing data

Cheng Yong Tang and Yongsong Qin
Biometrika (2012), pp. 1–7

We explore the use of estimating equations for efficient statistical inference in case of missing data. We propose a semi-parametric efficient empirical likelihood approach, and show that the empirical likelihood ratio statistic and its profile counterpart asymptotically follow central chi-square distributions when evaluated at the true parameter. The theoretical properties and practical performance of our approach are demonstrated through numerical simulations and data analysis.