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Full Text: YesSubject: search.filters.subject.Management science

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    PublicationOpen Access
    A machine learning approach for implementing data-driven production control policies
    (Taylor _ Francis, 2021) Department of Business Administration; N/A; Tan, Barış; Khayyati, Siamak; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 28600; N/A
    Given the extensive data being collected in manufacturing systems, there is a need for developing a systematic method to implement data-driven production control policies. For an effective implementation, first, the relevant information sources must be selected. Then, a control policy that uses the real-time signals collected from these sources must be implemented. We analyse the production control policy implementation problem in three levels: choosing the information sources, forming clusters of information signals to be used by the policy and determining the optimal policy parameters. Due to the search-space size, a machine-learning-based framework is proposed. Using machine learning speeds up optimisation and allows utilising the collected data with simulation. Through two experiments, we show the effectiveness of this approach. In the first experiment, the problem of selecting the right machines and buffers for controlling the release of materials in a production/inventory system is considered. In the second experiment, the best dispatching policy based on the selected information sources is identified. We show that selecting the right information sources and controlling a production system based on the real-time signals from the selected sources with the right policy improve the system performance significantly. Furthermore, the proposed machine learning framework facilitates this task effectively.
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    PublicationRestricted
    Multi-vehicle arc routing problems to restore post-disaster network connectivity
    (Koç University, 2016) Akbarighadikolaei, Vahid; Salman, Fatma Sibel; 0000-0001-6833-2552; Koç University Graduate School of Sciences and Engineering; Industrial Engineering and Operations Management; 178838
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    PublicationOpen Access
    Optimal sales and production rollover strategies under capacity constraints
    (Elsevier, 2021) Schwarz, Justus Arne; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600
    Firms regularly replace their old product generation by a newer generation to sustain and increase their market share and profit. The product rollover problem of deciding on the number of old products to be pre-produced before the introduction of the new generation, and then deciding on the prices, sales volumes, and production volumes of the old and the new generation during the introduction under capacity constraint is considered. Production capacity limitations are common during the introduction period of a new product. We provide the first study that examines how a production capacity constraint affects the optimal decisions. The optimal decisions for a deterministic period-based model are provided in closed-form. A single sales/production rollover strategy implies that the sales/production of the old generation is discontinued before introducing the new generation. With a dual sales/production rollover strategy, the old and the new generation are sold/produced simultaneously. Depending on the capacity shortage, there are two types of mitigation actions: (i) increasing the prices, (ii) changing the sales and/or production rollover strategies with pre-production while adjusting the prices accordingly. If the capacity is unlimited, aligned sales and production rollover strategies are always optimal. We establish the conditions under which limited capacity leads to a combination of a single production rollover with a dual sales rollover strategy. We show that the selection of optimal rollover strategies is non-monotone in the available capacity. This implies that a change in the rollover strategy in response to limiting capacity has to be revoked for more severe capacity shortages.
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    PublicationRestricted
    Recommendation systems: the strategic role of recommendations on retailers competition
    (Koç University, 2018) Bahani, Sofiane; Esseghaier, Skander; Koç University Graduate School of Business; Marketing