Authors:Hernan Caceres; Dongchen Yu; Alexander Nikolaev Pages: 405 - 427 Abstract: This paper addresses a multi-period production/inventory problem with two suppliers, where demand sizes and supplier lead time are stochastic and correlated. A discrete time, single item inventory system is considered, where inventory levels are reviewed periodically and managed using a base-stock policy. At the end of each period, a replenishment order is placed, which enters a queue at the buffer stage and is consequently forwarded to the first available supplier. We present a mathematical model of this inventory system and determine optimal safety stock levels for it, in closed form, using matrix analytic techniques and the properties of phase type distributions. To account for the effect of order crossovers, which occur whenever replenishment orders do not arrive in the sequence in which they were placed, the inventory shortfall distribution is analyzed. Finally, a set of numerical experiments with a system with two suppliers is presented, where the proposed model is compared to other existing models. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2764-8 Issue No:Vol. 271, No. 2 (2018)

Authors:Ben A. Chaouch Pages: 429 - 444 Abstract: The simple cash management problem includes the following considerations: the opportunity cost of holding too much cash versus the penalty cost of not having enough cash to meet current needs; the cost incurred (or profit generated) when making changes to cash levels by increasing or decreasing them when necessary; the uncertainty in timing and magnitude of cash receipts and cash disbursements; and the type of control policy that should be used to minimize the required level of cash balances and related costs. In this paper, we study a version of this problem in which cash receipts and cash disbursements occur according to two independent compound Poisson processes. The cash balance is monitored continuously and an order-point, order-up-to-level, and keep-level \( \left( {s, S, M} \right) \) policy is used to monitor the content, where \( s \le S \le M \) . That is, (a) if, at any time, the cash level is below s, an order is immediately placed to raise the level to S; (b) if the cash level is between s and M, no action is taken; (c) if the cash level is greater than M, the amount in excess of M is placed into an earning asset. We seek to minimize the expected total costs per unit time of running the cash balance. We use a level-crossing approach to develop a solution procedure for finding the optimal policy parameters and costs. Several numerical examples are given to illustrate the tradeoffs. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2822-2 Issue No:Vol. 271, No. 2 (2018)

Authors:Naoufel Cheikhrouhou; Biswajit Sarkar; Baishakhi Ganguly; Asif Iqbal Malik; Rafael Batista; Young Hae Lee Pages: 445 - 467 Abstract: To ensure all products as perfect, inspection is essential, even though it is not possible to inspect all products after producing them like some special type products as plastic joint for the water pipe. In this direction, this paper develops an inventory model with lot inspection policy. With the help of lot inspection, all products need not to be verified still the retailer can decide the quality of products during inspection. If retailer founds products as imperfect quality, the products are sent back to supplier. As it is lot inspection, mis-clarification errors (Type-I error and Type-II error) are introduced to model the problem. Two possible cases are discussed for sending back products as defective lots are immediately withdrawn from the system and send back to supplier with retailer’s payment and for second case, retailer sends defective products during receiving next lot from supplier with supplier’s investment, like in food industry or in hygiene product industry. The model is solved analytically and results indicate that optimal order size and sample size are intrinsically linked and maximize the total profit. Numerical examples, graphical representations, and sensitivity analysis are given to illustrate the model. The results suggest that sending defective products maintaining the first case is the more profitable than the second case. PubDate: 2018-12-01 DOI: 10.1007/s10479-017-2511-6 Issue No:Vol. 271, No. 2 (2018)

Authors:Phillip R. Jenkins; Matthew J. Robbins; Brian J. Lunday Pages: 641 - 678 Abstract: Military medical planners must develop dispatching policies that dictate how aerial medical evacuation (MEDEVAC) units are utilized during major combat operations. The objective of this research is to determine how to optimally dispatch MEDEVAC units in response to 9-line MEDEVAC requests to maximize MEDEVAC system performance. A discounted, infinite horizon Markov decision process (MDP) model is developed to examine the MEDEVAC dispatching problem. The MDP model allows the dispatching authority to accept, reject, or queue incoming requests based on a request’s classification (i.e., zone and precedence level) and the state of the MEDEVAC system. A representative planning scenario based on contingency operations in southern Afghanistan is utilized to investigate the differences between the optimal dispatching policy and three practitioner-friendly myopic policies. Two computational experiments are conducted to examine the impact of selected MEDEVAC problem features on the optimal policy and the system performance measure. Several excursions are examined to identify how the 9-line MEDEVAC request arrival rate and the MEDEVAC flight speeds impact the optimal dispatching policy. Results indicate that dispatching MEDEVAC units considering the precedence level of requests and the locations of busy MEDEVAC units increases the performance of the MEDEVAC system. These results inform the development and implementation of MEDEVAC tactics, techniques, and procedures by military medical planners. Moreover, an analysis of solution approaches for the MEDEVAC dispatching problem reveals that the policy iteration algorithm substantially outperforms the linear programming algorithms executed by CPLEX 12.6 with regard to computational effort. This result supports the claim that policy iteration remains the superlative solution algorithm for exactly solving computationally tractable Markov decision problems. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2760-z Issue No:Vol. 271, No. 2 (2018)

Authors:Wei Ma Pages: 787 - 809 Abstract: This note generalizes Gul and Pesendorfer’s random expected utility theory, a stochastic reformulation of von Neumann–Morgenstern expected utility theory for lotteries over a finite set of prizes, to the circumstances with a continuum of prizes. Let [0, M] denote this continuum of prizes; assume that each utility function is continuous, let \(C_0[0,M]\) be the set of all utility functions which vanish at the origin, and define a random utility function to be a finitely additive probability measure on \(C_0[0,M]\) (associated with an appropriate algebra). It is shown here that a random choice rule is mixture continuous, monotone, linear, and extreme if, and only if, the random choice rule maximizes some regular random utility function. To obtain countable additivity of the random utility function, we further restrict our consideration to those utility functions that are continuously differentiable on [0, M] and vanish at zero. With this restriction, it is shown that a random choice rule is continuous, monotone, linear, and extreme if, and only if, it maximizes some regular, countably additive random utility function. This generalization enables us to make a discussion of risk aversion in the framework of random expected utility theory. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2914-z Issue No:Vol. 271, No. 2 (2018)

Authors:Michele Monaci; André Gustavo dos Santos Pages: 831 - 851 Abstract: We consider a two-dimensional problem in which one is required to split a given rectangular bin into the smallest number of items. The resulting items must be squares to be packed, without overlapping, into the bin so as to cover all the given rectangle. We present a mathematical model and a heuristic algorithm that is proved to find the optimal solution in some special cases. Then, we introduce a relaxation of the problem and present different exact approaches based on this relaxation. Finally, we report computational experiments on the performances of the algorithms on a large set of randomly generated instances. PubDate: 2018-12-01 DOI: 10.1007/s10479-017-2746-2 Issue No:Vol. 271, No. 2 (2018)

Authors:Oleg Sokolinskiy; Benjamin Melamed; Ben Sopranzetti Pages: 971 - 997 Abstract: We consider a limited-liability firm that owns a finite single-product inventory subject to periodic-review replenishment and a corporate treasury that mediates the firm’s financial transactions related to inventory operations. The firm may elect to borrow money to purchase product via a revolving line of credit, secured by a compensating balance which determines the credit limit. The line of credit is subject to rollover risk, namely, each period the funding entity may, with some probability, refuse to roll over the line of credit. In response, the firm can search for an alternate funding entity, but in so doing it may incur search costs, primarily in the form of lost sales. The firm optimizes inventory replenishment order sizes and decides whether it should declare bankruptcy, as function of its inventory and available capital. The recent credit crunch has rendered illiquidity a critical concern for funding and operating decisions in enterprises. This paper addresses optimal inventory management in the face of liquidity shocks and supply disruptions. We show that rollover risk and supply disruption are important considerations for firms that rely on external funding. Rollover risk alone results in optimal inventory replenishment policies that differ materially from those specified by traditional supply chain models; differences manifest as state-dependent precautionary replenishment or cash hoarding. Inventory management models which fail to take rollover risk and supply disruption risk into account can prescribe suboptimal replenishment policies. Such policies would generate suboptimal profits for firms that rely on short-term financing to fund their working capital. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2965-1 Issue No:Vol. 271, No. 2 (2018)

Authors:Oleg Sokolinskiy; Benjamin Melamed; Ben Sopranzetti Pages: 999 - 999 Abstract: The original version of this article was revised as some author corrections were overlooked by vendor. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-3009-6 Issue No:Vol. 271, No. 2 (2018)

Authors:Xinyi Zhou; Yong Hu; Yong Deng; Felix T. S. Chan; Alessio Ishizaka Pages: 1045 - 1066 Abstract: Pairwise comparison matrix (PCM) as a crucial component of Analytic Hierarchy Process (AHP) presents the preference relations among alternatives. However, in many cases, the PCM is difficult to be completed, which obstructs the subsequent operations of the classical AHP. In this paper, based on decision-making and trial evaluation laboratory (DEMATEL) method which has ability to derive the total relation matrix from direct relation matrix, a new completion method for incomplete pairwise comparison matrix (iPCM) is proposed. The proposed method provides a new perspective to estimate the missing values in iPCMs with explicit physical meaning, which is straightforward and flexible. Several experiments are implemented as well to present the completion ability of the proposed method and some insights into the proposed method and matrix consistency. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2769-3 Issue No:Vol. 271, No. 2 (2018)

Authors:Baruch Mor; Gur Mosheiov Pages: 1079 - 1085 Abstract: We study a scheduling problem with the objective of minimizing total absolute deviation of completion times (TADC). TADC is considered here in the most general form studied so far: the machine setting is that of parallel unrelated, job processing time are assumed to be position-dependent with no restrictions on the functional form, and the option of processing only a subset of the jobs (i.e., job-rejection) is allowed. We show that minimizing TADC in this very general form remains polynomially solvable in the number of jobs. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2779-1 Issue No:Vol. 271, No. 2 (2018)

Authors:Sascha Kurz Pages: 1087 - 1089 Abstract: A proposal in a weighted voting game is accepted if the sum of the (nonnegative) weights of the “yea” voters is at least as large as a given quota. Several authors have considered representations of weighted voting games with minimum sum, where the weights and the quota are restricted to be integers. Here we correct the classification of all weighted voting games consisting of 9 voters which do not admit a unique minimum sum integer weight representation. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2893-0 Issue No:Vol. 271, No. 2 (2018)

Authors:Yves Crama; Michel Grabisch; Silvano Martello Pages: 3 - 10 Abstract: We introduce the series of Annals of Operations Research issues that collects updated versions of the invited surveys that appeared in the journal 4OR: A Quarterly Journal of Operations Research. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-3036-3 Issue No:Vol. 271, No. 1 (2018)

Authors:M. A. Goberna; M. A. López Pages: 237 - 278 Abstract: This paper reviews the state-of-the-art in the theory of deterministic and uncertain linear semi-infinite optimization, presents some numerical approaches to this type of problems, and describes a selection of recent applications in a variety of fields. Extensions to related optimization areas, as convex semi-infinite optimization, linear infinite optimization, and multi-objective linear semi-infinite optimization, are also commented. PubDate: 2018-12-01 DOI: 10.1007/s10479-018-2987-8 Issue No:Vol. 271, No. 1 (2018)

Authors:Kartick Dey; Debajyoti Chatterjee; Subrata Saha; Ilkyeong Moon Abstract: Joint determination of price, rebate, investment in preservation technology, and order quantity is a complex task for retailers today. To help retailers, this paper presents an investigation on a replenishment policy for deteriorating products that focused on the choice between dynamic and static rebates under the price, displayed stock level, and rebate-induced demand. With the objective of maximizing the retailer’s profit, six different models were formulated under static and dynamic environments to identify optimal price-and-rebate pair and preservation technology investment policy. Optimal control theory was employed to determine the rate of dynamic rebate. A hybrid bat algorithm (HBA) is developed to find solutions for the proposed non-linear optimization problems. The efficiency of the proposed algorithm was verified with standard test functions. Price sensitivity, the nature of the product, and display stock elasticity were found to be decisive parameters for a retailer’s rebate strategy. Dynamic rebate on initial price of the product can significantly improve the profit of the retailer. The retailer’s investment decision was also significantly influenced by the nature of the product. Sensitivity analyses were carried out to offer managerial insights. PubDate: 2018-12-10 DOI: 10.1007/s10479-018-3110-x

Authors:Xiaohong Liu; Jiasen Sun; Feng Yang; Jie Wu Abstract: This study explored how dramatic changes in ownership structure and operational technologies have influenced Chinese bank efficiency over the past decade. The study included an empirical analysis using 5 years (2011–2015) of operational data for 71 Chinese commercial banks. Two two-stage meta-frontier data envelopment analysis network models and multiple regression models were used to estimate and analyze impacts of variations in bank ownership structure. The main empirical results show that irrespective of deposits or loans efficiency, State-owned Banks (SOBs) have the highest technology and management levels. In contrast, City Commercial Banks should improve both technology and management levels, narrowing the gap with SOBs and Joint-stock Banks. The deposit efficiency of a bank was found to be mainly influenced by the nature of ownership (national shareholding ratio and the shareholding ratio of the domestic legal entities) and ownership concentration. The loan efficiency of a bank was mainly affected by the nature of ownership (the shareholding ratio of the foreign legal entities) and ownership liquidity. PubDate: 2018-12-10 DOI: 10.1007/s10479-018-3106-6

Authors:Han Lin Shang; Yang Yang; Fearghal Kearney Abstract: As a forward-looking measure of future equity market volatility, the VIX index has gained immense popularity in recent years to become a key measure of risk for market analysts and academics. We consider discrete reported intraday VIX tick values as realisations of a collection of curves observed sequentially on equally spaced and dense grids over time and utilise functional data analysis techniques to produce 1-day-ahead forecasts of these curves. The proposed method facilitates the investigation of dynamic changes in the index over very short time intervals as showcased using the 15-s high-frequency VIX index values. With the help of dynamic updating techniques, our point and interval forecasts are shown to enjoy improved accuracy over conventional time series models. PubDate: 2018-12-07 DOI: 10.1007/s10479-018-3108-4

Authors:Khaled Elbassioni; Areg Karapetyan; Trung Thanh Nguyen Abstract: Stimulated by salient applications arising from power systems, this paper studies a class of non-linear Knapsack problems with non-separable quadratic constrains, formulated in either binary or integer form. These problems resemble the duals of the corresponding variants of 2-weighted Knapsack problem (a.k.a., complex-demand Knapsack problem) which has been studied in the extant literature under the paradigm of smart grids. Nevertheless, the employed techniques resulting in a polynomial-time approximation scheme (PTAS) for the 2-weighted Knapsack problem are not amenable to its minimization version. We instead propose a greedy geometry-based approach that arrives at a quasi PTAS (QPTAS) for the minimization variant with boolean variables. As for the integer formulation, a linear programming-based method is developed that obtains a PTAS. In view of the curse of dimensionality, fast greedy heuristic algorithms are presented, additionally to QPTAS. Their performance is corroborated extensively by empirical simulations under diverse settings and scenarios. PubDate: 2018-12-06 DOI: 10.1007/s10479-018-3111-9

Authors:Hossein Soltani; Babak Moazzez Abstract: Spread of influence in a network can be modeled and studied within the concept of dynamic monopolies in graphs. We give an integer programming formulation for finding a minimum dynamic monopoly in an undirected graph. The corresponding 0–1 polytope and its facets are studied and several families of facet defining inequalities are introduced. Computational experiments have been performed to show the strength of the IP formulation and its facet defining inequalities. PubDate: 2018-12-06 DOI: 10.1007/s10479-018-3107-5

Authors:Jianghua Zhang; Yang Liu; Yingxue Zhao; Tianhu Deng Abstract: Disasters such as earthquake or tsunami can easily take the lives of thousands of people and millions worth of property in a fleeting moment. A successful emergency evacuation plan is critical in response to disasters. In this paper, we seek to investigate the multi-source, multi-destination evacuation problem. First, we construct a mixed integer linear programming model. Second, based on K shortest paths and user equilibrium, we propose a novel algorithm (hereafter KPUE), whose complexity is polynomial in the numbers of nodes and evacuees. Finally, we demonstrate the effectiveness of algorithm KPUE by a real evacuation network in Shanghai, China. The numerical examples show that the average computation time of the proposed algorithm is 95% less than that of IBM ILOG CPLEX solver and the optimality gap is no more than 5%. PubDate: 2018-12-06 DOI: 10.1007/s10479-018-3102-x