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Publication Metadata only A general test for SSD portfolio efficiency(Springer, 2015) Kopa, Milos; N/A; Post, Gerrit Tjeerd; Other; Graduate School of Business; N/AWe develop and implement a Linear Programming test to analyze whether a given investment portfolio is efficient in terms of second-order stochastic dominance relative to all possible portfolios formed from a set of base assets. In case of efficiency, the primal model identifies a sub-gradient vector of a utility function that rationalizes the evaluated portfolio. In case of inefficiency, the dual model identifies a second, efficient portfolio that dominates the evaluated portfolio. The test gives a general necessary and sufficient condition, and can deal with general linear portfolio restrictions, inefficiency degree measures, and scenarios with unequal probabilities. We also develop a compact version of the test that substantially reduces computational burden at the cost of losing information about the dual dominating portfolio in case of inefficiency. An application to US investment benchmark data qualifies a broad stock market index as significantly inefficient, and suggests that no risk-averse investor would hold the market index in the face of attractive premiums offered by some more concentrated investment portfolios.Publication Metadata only A min-max-sum resource allocation problem and its applications(Informs, 2001) Kouvelis, P.; Yu, G.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819In this paper we consider a class of discrete resource-allocation problems with a min-max-sum objective function. We first provide several examples of practical applications of this problem. We then develop a branch-and-bound procedure for solving the general case of this computationally intractable problem. The proposed solution procedure employs a surrogate relaxation technique to obtain lower and upper bounds on the optimal objective function value of the problem. To obtain the multipliers of the surrogate relaxation, two alternative approaches are discussed. We also discuss a simple approximation algorithm with a tight bound. Our computational results support the effectiveness of the branch-and-bound procedure for fairly large-size problems.Publication Metadata only Advance demand information and a restricted production capacity: on the optimality of order base-stock policies(Springer, 2007) Wijngaard, Jacob; Department of Industrial Engineering; Karaesmen, Fikri; Faculty Member; Department of Industrial Engineering; College of Engineering; 3579This paper considers the optimality of order aggregation in a single-item production/inventory problem with advance demand information and a restricted production capacity. The advance demand information is modeled by introducing a positive customer order lead time. The paper proves, when customer order lead times are less than a threshold value, it is allowed to aggregate the orders over time when establishing the optimal production decision. This implies the optimality of an order base-stock policy. It shows also that in case of linear inventory cost, the positive effect of advance demand information is equal to a cost reduction that is proportional to idle time and foreknowledge horizon. The results hold for the backlogging case as well as for the lost-sales case.Publication Metadata only An adaptive and diversified vehicle routing approach to reducing the security risk of cash-in-transit operations(Wiley, 2017) Bozkaya, Burçin; Department of Industrial Engineering; N/A; Salman, Fatma Sibel; Telciler, Kaan; Faculty Member; Master Student; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 178838; N/AWe consider the route optimization problem of transporting valuables in cash-in-transit (CIT) operations. The problem arises as a rich variant of the capacitated vehicle routing problem (CVRP) with time windows and pickup and deliveries. Due to the high-risk nature of this operation (e.g., robberies) we consider a bi-objective function where we attempt to minimize the total transportation cost and the security risk of transporting valuables along the designed routes. For risk minimization, we propose a composite risk measure that is a weighted sum of two risk components: (i) following the same or very similar routes, and (ii) visiting neighborhoods with low socioeconomic status along the routes. We also consider vehicle capacities in terms of monetary value carried as per insurance regulations. We develop an adaptive randomized bi-objective path selection algorithm that uses the composite risk measure in choosing alternative paths between origin-destination pairs over a sequence of days. We solve the rich CVRP approximately for each day with updated costs. We test our solution approach on a data set from a CIT delivery service provider and provide insights on how the routes diversify daily. Our approach generates a spectrum of solutions with costrisk trade-off to support decision making.Publication Metadata only An EOQ model with multiple suppliers and random capacity(Wiley, 2006) Erdem, Aslı Sencer; Fadıloğlu, Mehmet Murat; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631We consider an EOQ model with multiple suppliers that have random capacities, which leads to uncertain yield in orders. A given order is fully received from a supplier if the order quantity is less than the supplier's capacity; otherwise. the quantity received is equal to the available capacity. The optimal order quantities for the suppliers can be obtained as the unique solution of an implicit set of equations in which the expected unsatisfied order is the same for each supplier. Further characterizations and properties are obtained for the uniform and exponential capacity cases with discussions on the issues related to diversification among suppliers.Publication Metadata only Coordinated pricing and inventory decisions for perishable products(Springer, 2017) Kaya, Onur; N/A; Polat, Aylin Lelizar; Master Student; Graduate School of Sciences and Engineering; N/AWe investigate the problem of jointly determining the optimal pricing and inventory replenishment strategy for a deterministic perishable inventory system in which demand is time and price dependent. The inventory is also assumed to decay at a certain rate. The seller has the opportunity to adjust prices for a discrete number of times at a certain cost during the sales season to influence demand and to improve revenues. We develop a mathematical model to find the optimal times to change the prices, the optimal prices and the optimal order quantity. We present analytical results to find the optimal prices when the times of price changes are given and design heuristic algorithms to determine the optimal times to change the prices. We analyze the efficiency of multiple pricing strategy by comparing the profits obtained by single pricing case and also analyze the effect of different parameters on the optimal solution through numerical experiments.Publication Metadata only DNA sequencing by hybridization via genetic search(2006) Blazewicz, Jacek; Swiercz, Aleksandra; Weglarz, Jan; Department of Industrial Engineering; Oğuz, Ceyda; Faculty Member; Department of Industrial Engineering; College of Engineering; 6033An innovative approach to DNA sequencing by hybridization utilizes isothermic oligonucleotide libraries. In this paper, we demonstrate the utility of a genetic algorithm for the combinatorial portion of this new approach by incorporating characteristics of DNA sequencing by hybridization in addition to isothermic oligonucleotide libraries. Specialized crossover and mutation operators were developed for this purpose. After initial experiments for parameter adjustment, the performance of the genetic algorithm approach was evaluated with respect to previous methods in the literature. The results indicate that the proposed new approach is superior to previous approaches. The proposed new crossover operator that inherits some features of the structured weighted combinations might also be of value for some other combinatorial problems, including the traveling salesman problem.Publication Metadata only Hedging demand and supply risks in the newsvendor model(Springer, 2015) N/A; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Okyay, Hayrettin Kaan; Karaesmen, Fikri; Özekici, Süleyman; Master Student; Faculty Member; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 3579; 32631We consider a single-period inventory model where there are risks associated with the uncertainty in demand as well as supply. Furthermore, the randomness in demand and supply is correlated with the financial markets. Recent literature provides ample evidence on this issue. The inventory manager may then exploit this correlation and manage his risks by investing in a portfolio of financial instruments. The decision problem, therefore, includes not only the determination of the optimal ordering policy, but also the selection of the optimal portfolio at the same time. We analyze this problem in detail and provide a risk-sensitive approach to inventory management where one considers both the mean and the variance of the resulting cash flow. The analysis results in some interesting and explicit characterizations on the structure of the optimal policy.Publication Metadata only Inventory control and pricing for perishable products under age and price dependent stochastic demand(Springer, 2018) Kaya, Onur; N/A; Ghahroodi, Sajjad Rahimi; Master Student; Graduate School of Sciences and Engineering; N/APerishable products have a short lifetime and cause a high amount of wastage when managed ineffectively, due to their deterioration over time. We consider coordinated inventory and pricing decisions for perishable products in a periodically-reviewed inventory system with an age and price dependent random demand. We consider the products with a fixed shelf lifetime and use dynamic programming to model this system. We prove certain structural characteristics of the optimal solution and also analyze the effect of different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement inventory control policies, namely quantity-based and age-based policies, and investigate their effectiveness.Publication Metadata only Mathematical programming representations of the dynamics of continuous-flow production systems(Taylor & Francis Inc, 2015) Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600This study presents a mathematical programming representation of discrete-event systems with a continuous time and mixed continuous-discrete state space. In particular, continuous material flow production systems are considered. A mathematical programming representation is used to generate simulated sample realizations of the system and also to optimize control parameters. The mathematical programming approach has been used in the literature for performance evaluation and optimization of discrete material flow production systems. In order to show the applicability of the same approach to continuous material flow systems, this article focuses on optimal production flow rate control problems for a continuous material flow system with an unreliable station and deterministic demand. These problems exhibit most of the dynamics observed in various continuous flow productions systems: flow dynamics, machine failures and repairs, changing flow rates due to system status, and control. Moreover, these problems include decision variables related to the control policies and different objective functions. By analyzing the backlog, lost sales, and production and subcontracting rate control problems, it is shown that a mixed-integer linear programming formulation with a linear objective function and linear constraints can be developed to determine the simulated performance of the system. The optimal value of the control policy that optimizes an objective function that includes the estimated expected inventory carrying and backlog cost and also the revenue through sales can also be determined by solving a quadratic integer program with a quadratic objective function and linear constraints. As a result, it is shown that the mathematical programming representation is also a viable method for performance evaluation and optimization of continuous material production systems.