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Barrera, J., Carrasco, R. A., Mondschein, S., Canessa, G., & RojasZalazar, D. (2020). Operating room scheduling under waiting time constraints: the Chilean GES plan. Ann. Oper. Res., 286(12), 501–527.
Abstract: In 2000, Chile introduced profound health reforms to achieve a more equitable and fairer system (GES plan). The reforms established a maximum waiting time between diagnosis and treatment for a set of diseases, described as an opportunity guarantee within the reform. If the maximum waiting time is exceeded, the patient is referred to another (private) facility and receives a voucher to cover the additional expenses. This voucher is paid by the health provider that had to do the procedure, which generally is a public hospital. In general, this reform has improved the service for patients with GES pathologies at the expense of patients with nonGES pathologies. These new conditions create a complicated planning scenario for hospitals, in which the hospital's OR Manager must balance the fulfillment of these opportunity guarantees and the timely service of patients not covered by the guarantee. With the collaboration of the Instituto de Neurocirugia, in Santiago, Chile, we developed a mathematical model based on stochastic dynamic programming to schedule surgeries in order to minimize the cost of referrals to the private sector. Given the large size of the state space, we developed an heuristic to compute good solutions in reasonable time and analyzed its performance. Our experimental results, with both simulated and real data, show that our algorithm performs close to optimum and improves upon the current practice. When we compared the results of our heuristic against those obtained by the hospital's OR manager in a simulation setting with real data, we reduced the overtime from occurring 21% of the time to zero, and the nonGES average waiting list's length from 71 to 58 patients, without worsening the average throughput.
Keywords: Scheduling; Operating theater; Operating room scheduling

Barrera, J., Moreno, E., & Varas, S. (2020). A decomposition algorithm for computing income taxes with passthrough entities and its application to the Chilean case. Ann. Oper. Res., 286(12), 545–557.
Abstract: Income tax systems with “passthrough” entities transfer a firm's income to shareholders, which are taxed individually. In 2014, a Chilean tax reform introduced this type of entity and changed to an accrual basis that distributes incomes (but not losses) to shareholders. A crucial step for the Chilean taxation authority is to compute the final income of each individual given the complex network of corporations and companies, usually including cycles between them. In this paper, we show the mathematical conceptualization and the solution to the problem, proving that there is only one way to distribute income to taxpayers. Using the theory of absorbing Markov chains, we define a mathematical model for computing the taxable income of each taxpayer, and we propose a decomposition algorithm for this problem. This approach allows us to compute the solution accurately and to efficiently use computational resources. Finally, we present some characteristics of Chilean taxpayers' network and the computational results of the algorithm using this network.
Keywords: Income taxes; Markov processes; Networks; Algorithms

de Mateo, F., Coelli, T., & O'Donnell, C. (2006). Optimal paths and costs of adjustment in dynamic DEA models: with application to chilean department stores. Ann. Oper. Res., 145(1), 211–227.
Abstract: In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, nonstatic output quantities, nonstatic input prices, and nonstatic costs of adjustment, technological change, quasifixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA modelsthey identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are nonzero.
Keywords: cost of adjustment; dynamic DEA; path of adjustment

Espinoza, D., Goycoolea, M., Moreno, E., & Newman, A. (2013). MineLib: a library of open pit mining problems. Ann. Oper. Res., 206(1), 93–114.
Abstract: Similar to the mixedinteger programming library (MIPLIB), we present a library of publicly available test problem instances for three classical types of open pit mining problems: the ultimate pit limit problem and two variants of open pit production scheduling problems. The ultimate pit limit problem determines a set of notional threedimensional blocks containing ore and/or waste material to extract to maximize value subject to geospatial precedence constraints. Open pit production scheduling problems seek to determine when, if ever, a block is extracted from an open pit mine. A typical objective is to maximize the net present value of the extracted ore; constraints include precedence and upper bounds on operational resource usage. Extensions of this problem can include (i) lower bounds on operational resource usage, (ii) the determination of whether a block is sent to a waste dump, i.e., discarded, or to a processing plant, i.e., to a facility that derives salable mineral from the block, (iii) average grade constraints at the processing plant, and (iv) inventories of extracted but unprocessed material. Although open pit mining problems have appeared in academic literature dating back to the 1960s, no standard representations exist, and there are no commonly available corresponding data sets. We describe some representative open pit mining problems, briefly mention related literature, and provide a library consisting of mathematical models and sets of instances, available on the Internet. We conclude with directions for use of this newly established mining library. The library serves not only as a suggestion of standard expressions of and available data for open pit mining problems, but also as encouragement for the development of increasingly sophisticated algorithms.

Gonzalez, E., Epstein, L. D., & Godoy, V. (2012). Optimal number of bypasses: minimizing cost of calls to wireless phones under Calling Party Pays. Ann. Oper. Res., 199(1), 179–191.
Abstract: In telecommunications, Calling Party Pays is a billing formula that prescribes that the person who makes the call pays its full cost. Under CPP landline to wireless phone calls have a high cost for many organizations. They can reduce this cost at the expense of installing wireless bypasses to replace landline to wireless traffic with wirelesstowireless traffic, when the latter is cheaper than the former. Thus, for a given timehorizon, the cost of the project is a tradeoff between traffic towireless and the number of bypasses. We present a method to determine the number of bypasses that minimizes the expected cost of the project. This method takes into account hourly varying traffic intensity. Our method takes advantage of parallels with inventory models for rental items. Examples illustrate the economic value of our approach.

Moreno, S., Pereira, J., & Yushimito, W. (2020). A hybrid Kmeans and integer programming method for commercial territory design: a case study in meat distribution. Ann. Oper. Res., 286(12), 87–117.
Abstract: The objective of territorial design for a distribution company is the definition of geographic areas that group customers. These geographic areas, usually called districts or territories, should comply with operational rules while maximizing potential sales and minimizing incurred costs. Consequently, territorial design can be seen as a clustering problem in which clients are geographically grouped according to certain criteria which usually vary according to specific objectives and requirements (e.g. costs, delivery times, workload, number of clients, etc.). In this work, we provide a novel hybrid approach for territorial design by means of combining a Kmeansbased approach for clustering construction with an optimization framework. The Kmeans approach incorporates the novelty of using tour length approximation techniques to satisfy the conditions of a pork and poultry distributor based in the region of Valparaiso in Chile. The resulting method proves to be robust in the experiments performed, and the Valparaiso case study shows significant savings when compared to the original solution used by the company.
Keywords: Territorial design; Clustering; Kmeans; Integer programming; Case study
