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Publication Metadata only A fuzzy decomposition method for multistation production systems subject to blocking(Elsevier Science Bv, 1996) Yeralan, Sencer; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600This study presents a new methodology to adjust the value of the proportionality constant (step length parameter) used in the general decomposition method for multistation heterogeneous production systems proposed in an earlier study for specially unbalanced production systems by using fuzzy logic control. The decomposition method is based on successive approximations. Namely, input rate to each subsystem is adjusted proportional to the difference in production rates of adjacent stations. This process continues until all the subsystems have the same production rate, Fuzzy logic control uses basic observations described in linguistic variables of how production rate changes as a function of input rate, Consequently, the proportionality constant in the successive approximation method is adjusted. These observations are not model specific, Thus, the fuzzy decomposition method can be applied to a wide variety of production systems. The same methodology can also be used in other applications where adjusting the step length parameter to attain the highest convergence rate is not trivial. For example, step length parameter used in subgradient optimization and other search methodologies can also be adjusted by using the fuzzy logic control methodology presented in this study. Numerical experience shows that this method yields a substantial improvement in the convergence rate of the decomposition method for highly unbalanced production system.Publication Metadata only A lab-scale manufacturing system environment to investigate data-driven production control approaches(Elsevier Sci Ltd, 2021) N/A; N/A; Department of Business Administration; Khayyati, Siamak; Tan, Barış; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 28600Controlling production and release of material into a manufacturing system effectively can lower work-inprogress inventory and cycle time while ensuring the desired throughput. With the extensive data collected from manufacturing systems, developing an effective real-time control policy helps achieving this goal. Validating new control methods using the real manufacturing systems may not be possible before implementation. Similarly, using simulation models can result in overlooking critical aspects of the performance of a new control method. In order to overcome these shortcomings, using a lab-scale physical model of a given manufacturing system can be beneficial. We discuss the construction and the usage of a lab-scale physical model to investigate the implementation of a data-driven production control policy in a production/inventory system. As a datadriven production control policy, the marking-dependent threshold policy is used. This policy leverages the partial information gathered from the demand and production processes by using joint simulation and optimization to determine the optimal thresholds. We illustrate the construction of the lab-scale model by using LEGO Technic parts and controlling the model with the marking-dependent policy with the data collected from the system. By collecting data directly from the lab-scale production/inventory system, we show how and why the analytical modeling of the system can be erroneous in predicting the dynamics of the system and how it can be improved. These errors affect optimization of the system using these models adversely. In comparison, the datadriven method presented in this study is considerably less prone to be affected by the differences between the physical system and its analytical representation. These experiments show that using a lab-scale manufacturing system environment is very useful to investigate different data-driven control policies before their implementation and the marking-dependent threshold policy is an effective data-driven policy to optimize material flow in manufacturing systems.Publication Metadata only A min-sum-max resource allocation problem(Kluwer Academic Publ, 2000) Kouvelis, P.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819In this paper we describe a class of resource allocation problems with a min–sum–max objective function. We first discuss practical applications of the problem. We then present a result on the computational complexity of the problem. We propose an implicit enumeration procedure for solving the general case of the problem, and report on our computational experience with the solution procedure.Publication Metadata only A near-optimal order-based inventory allocation rule in an assemble-to-order system and its applications to resource allocation problems(Springer, 2005) Xu, Susan Hong; Department of Business Administration; Akçay, Yalçın; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51400Assemble-to-order (ATO) manufacturing strategy has taken over the more traditional make-to-stock (MTS) strategy in many high-tech firms. ATO strategy has enabled these firms to deliver customized demand timely and to benefit from risk pooling due to component commonality. However, multi-component, multi-product ATO systems pose challenging inventory management problems. In this chapter, we study the component allocation problem given a specific replenishment policy and realized customer demands. We model the problem as a general multidimensional knapsack problem (MDKP) and propose the primal effective capacity heuristic (PECH) as an effective and simple approximate solution procedure for this NP-hard problem. Although the heuristic is primarily designed for the component allocation problem in an ATO system, we suggest that it is a general solution method for a wide range of resource allocation problems. We demonstrate the effectiveness of the heuristic through an extensive computational study which covers problems from the literature as well as randomly generated instances of the general and 0-1 MDKP. In our study, we compare the performance of the heuristic with other approximate solution procedures from the ATO system and integer programming literature.Publication Metadata only Cyclic scheduling in synchronous production lines(Taylor & Francis, 1999) Kouvelis, P.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819In this paper we address the scheduling problem in unpaced synchronous mixed-model production lines operated under a cyclic scheduling policy. We first discuss operations of a production line with the synchronous transfer of parts. We then present an integer programming formulation of the problem. The problem, however, is NP-hard, and for its exact solution we propose an implicit enumeration scheme. We discuss a property of the scheduling problem which allows us to effectively solve large size instances of the problem. We also present an approximate solution procedure with very good average performance. Useful managerial insights are obtained as we search for ways to improve the performance of synchronous lines. The relaxation of one of our original assumptions in the scheduling problem formulation results in an easy problem whose solution generates the absolute best in throughput performance configuration of the production line. Implementation of this solution, however, requires increasing the number of buffers in the line. We suggest other performance improvement ways to better balance the tradeoff between throughput and average Work-In-Progress (WIP) inventory in the line.Publication Metadata only Flow-line scheduling problem with controllable processing times(Taylor & Francis, 1997) Kouvelis, P.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819In this paper we address the simultaneous scheduling and optimal-processing-times selection problem in a multi-product deterministic flow line operated under a cyclic scheduling approach. The selection of processing times plays an important role in achieving the desired production rate with the least possible operating cost. We first formulate the important subproblem of optimal-processing-times selection for different objectives, when the sequence of jobs is fixed, and then develop an efficient solution procedure for it. The fast solution of the fixed sequence problem is necessary for the development of efficient approximate solution procedures for the simultaneous scheduling and optimal-processing-times problem. A computational study on the effectiveness of the proposed solution procedure is presented. For the solution of the simultaneous scheduling and optimal-processing-times problem we suggest an iterative solution procedure, and report our computational experience with this procedure. For the solution of large problems we present a genetic algorithm. The effectiveness of the algorithm is demonstrated through computational results and by evaluating the performance of the obtained solutions against lower bounds that we developed for the problem.Publication Metadata only It won't fit! for innovative products, sometimes that's for the best(Wiley, 2015) Stanko, Michael A.; Molina-Castillo, Francisco-Jose; Department of Business Administration; Harmancıoğlu, Nükhet; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 123423The degree of overlap (i.e., fit) between product development organizations' resources and the product development projects pursued has powerful performance implications. Drawing on organizational learning theory and the resource-based view, this research conceptualizes and empirically tests the interrelationships between the levels of fit, innovativeness, speed to market, and financial new product performance. After reviewing the research literature relevant to resource fit and new product performance, the level of innovativeness is posited to be an important moderating and mediating factor, which is validated by analysis of data gathered from 279 product developing firms. Technological fit has a negative direct effect on both technological and market innovativeness, while the use of existing marketing resources (i.e., a high degree of marketing fit) positively impacts technological innovativeness. This suggests, consistent with findings from market orientation research, that a deep, long-held customer understanding can promote technological innovativeness. The moderating hypotheses proposed are also well supported: First, a high degree of marketing fit has a more positive impact on performance for market innovative products (e.g., products which address a new target market or use a nontraditional channel for the firm). Drawing on a deep customer understanding is more critical to performance for market innovative products. Conversely, the benefits of marketing fit are limited where market innovativeness is lacking. Interestingly, the counterpart moderating role of technological innovativeness on technological fit's performance effect is not significant; the level of technological innovativeness does not significantly impact the performance impact of technological fit. There are also significant moderating effects across dimensions. Our results show that the financial benefit of using existing marketing resources is lessened for technologically innovative products. Technological innovations necessitate drastic adaptation of marketing resources (i.e., channel and brand); firms drawing only on existing marketing resources for a technologically innovative new product will incur reduced profit. Similarly, the positive implications of using existing technological resources are limited for products which are highly market innovative. Generally, resource fit is seen to have an (oft-overlooked) dark side in product development, though several of our findings suggest that marketing resources are more flexible than are technological resources.Publication Metadata only Loss of customer goodwill in the uncapacitated lot-sizing problem(Pergamon-Elsevier Science Ltd, 2007) Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308Loss of customer goodwill in uncapacitated single level lot-sizing is studied with a mixed integer programming model extending the well-known Wagner-Whitin (WW) model. The objective is to maximize profit from production and sales of a single good over a finite planning horizon. Demand, costs, and prices vary with time. Unsatisfied demand cannot be backordered. It leads to the immediate loss of profit from sales. Previous models augment the total cost objective by this lost profit. The difference of the proposed model is that unsatisfied demand in a given period causes the demand in the next period to shrink due to the loss of customer goodwill. A neighborhood search and restoration heuristic is developed that tries to adjust the optimal lot sizes of the original no-goodwill-loss model to the situation with goodwill loss. Its performance is compared with the WW solution, and with the commercial solver CPLEX 8.1 on 360 test problems of various period lengths. (c) 2005 Elsevier Ltd. All rights reserved.Publication Metadata only Modeling and analysis of a cooperative service network(Pergamon-Elsevier Science Ltd, 2021) N/A; N/A; Department of Business Administration; Hosseini, Behnaz; Tan, Barış; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 28600With the advances in technology and changes in customers' attitude towards different service delivery formats, it is important for the service providers to deliver online services in addition to the traditional face-to-face services. In the cooperative service network presented in this study, service providers cooperate to serve online service requests received by the network in addition to their own customers. Designing and managing the cooperative network effectively increase the utilization of the involved servers, provide an adequate service for the external customers, and increase the profit for both the network and service providers. From the operational perspective, the number and utilization of the members to be included in the network and the price that will be paid to each member for a directed request are the main design questions. In order to answer these questions, we present a stochastic model that captures the dynamics of customer arrivals, assignment, and admission control. To establish this model, we first derive the solution of the dynamic admission control problem for the servers who decide how to admit their own customers and the external online customers using a Markov decision process. We then analyze the operation of the whole network with the servers who use the optimal admission control policy and obtain the system performance measures depending on the members' operational parameters. These results are used to determine the optimal number of servers in the network and the service price to be paid to the participating servers in order to maximize the obtained profit. We show that a cooperative service network is an effective way of utilizing the idle capacity of the servers while providing an adequate service level for the external online customers and increasing the profit for both the network and service providers.Publication Metadata only Multi-product newsvendor problem with value-at-risk considerations(Elsevier Science Bv, 2009) Özler, Aysun; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; 3579We consider the single period stochastic inventory (newsvendor) problem with downside risk constraints. The aim in the classical newsvendor problem is maximizing the expected profit. This formulation does not take into account the risk of earning less than a desired target profit or losing more than an acceptable level due to the randomness of demand. We utilize Value at Risk (VaR) as the risk measure in a newsvendor framework and investigate the multi-product newsvendor problem under a VaR constraint. To this end, we first derive the exact distribution function for the two-product newsvendor problem and develop an approximation method for the profit distribution of the N-product case (N>2). A mathematical programming approach is used to determine the solution of the newsvendor problem with a VaR constraint. This approach allows us to handle a wide range of cases including the correlated demand case that yields new results and insights. The accuracy of the approximation method and the effects of the system parameters on the Solution are investigated numerically.