Researcher:
Ünsal, Özgür

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Özgür

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Ünsal

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Ünsal, Özgür

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2013 - 201922020 - 20213

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Researcher Of Publications: search.filters.isAuthorOfPublication.412a6c14-38ed-40fa-be84-1e49fd5fca0e

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    Constraint programming approach to quay crane scheduling problem
    (Pergamon-Elsevier Science Ltd, 2013) N/A; N/A; Department of Industrial Engineering; Ünsal, Özgür; Oğuz, Ceyda; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 328856; 6033
    This study presents a constraint programming (CP) model for the quay crane scheduling problem (QCSP), which occurs at container terminals, with realistic constraints such as safety margins, travel times and precedence relations. Next, QCSP with time windows and integrated crane assignment and scheduling problem, are discussed. The performance of the CP model is compared with that of algorithms presented in QCSP literature. The results of the computational experiments indicate that the CP model is able to produce good results while reducing the computational time, and is a robust and flexible alternative for different types of crane scheduling problems.
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    An extended formulation of moldable task scheduling problem and its application to quay crane assignments
    (Pergamon-Elsevier Science Ltd, 2021) Ünsal, Özgür; PhD Student; Graduate School of Sciences and Engineering; N/A
    In this paper, we study an extended formulation of moldable task scheduling problem (MTSP) motivated by the assignments of quay cranes to vessels. In container terminals, handling time of a vessel depends on the number of quay cranes assigned to that vessel. This characteristic allows us to model quay crane assignment problem (QCAP) as a variant of MTSP. By considering the modeling requirements of various properties of QCAP, we develop an extended formulation of MTSP with specific task to machine assignments. Even though this formulation brings modeling flexibility, it can only be solved for small instances because of its size. For this reason, we provide a generic solution algorithm based on a logic based Benders decomposition by utilizing the extended formulation. There are various characteristics of QCAP observed in different terminals. Accordingly, we implement the proposed decomposition algorithm for contiguous assignments of QCs, uniform QCs as well as the availability of QCs. Computational experiments show that the proposed algorithm is able to solve instances of considerable sizes to optimality and provides a modeling flexibility that allows implementation to different terminal settings.
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    Reclaimer scheduling in dry bulk terminals
    (IEEE-inst Electrical Electronics Engineers inc, 2020) Ünsal, Özgür; PhD Student; Graduate School of Sciences and Engineering; N/A
    This paper studies a complex parallel scheduling problem with non-crossing constraint, sequence dependent setup times, eligibility restrictions, and precedence relationships motivated by reclaimer scheduling in dry bulk terminals. in a stockyard of any dry bulk terminal, stockpiles are handled by reclaimers. therefore, improving the operational efficiency of reclaimers is critical for the overall performance of these terminals which are struggling with increasing workload. We study the variants of this problem with and without stacking operations. for each variant, we present a lower and an upper bound. a strong lower bound is obtained by relaxing the non-crossing constraint and solving the resulting problem to the optimality. While this relaxation still addresses a challenging scheduling problem, proposed arc-time-indexed formulation copes with the instances of practical size. We develop a novel constraint programming formulation to provide an upper bound for the problem. Computational experiments show this robust approach is able to generate near-optimal schedules for different stockyard configurations within a minute.
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    An exact algorithm for integrated planning of operations in dry bulk terminals
    (Pergamon-Elsevier Science Ltd, 2019) N/A; Department of Industrial Engineering; Ünsal, Özgür; Oğuz, Ceyda; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; 328856; 6033
    We consider integrated planning problem of export dry bulk terminals. This problem consists of three important operations: (i) berth allocation, (ii) reclaimer scheduling, and (iii) stockyard allocation, and includes tidal time windows, multiple stocking pads and non-crossing of reclaimers. We exploit relationships among these operations to decompose this complex problem and propose a logic-based Benders decomposition algorithm. Master and subproblems are modeled with mixed-integer programming and constraint programming, respectively, such that complementary strengths of these programming paradigms are utilized. Computational experiments show that the proposed method can effectively solve the integrated problem for up to two weeks of planning horizon.
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    PublicationOpen Access
    Reclaimer scheduling in dry bulk terminals
    (Institute of Electrical and Electronics Engineers (IEEE), 2020) N/A; Ünsal, Özgür; Graduate School of Sciences and Engineering
    This paper studies a complex parallel scheduling problem with non-crossing constraint, sequence dependent setup times, eligibility restrictions, and precedence relationships motivated by reclaimer scheduling in dry bulk terminals. In a stockyard of any dry bulk terminal, stockpiles are handled by reclaimers. Therefore, improving the operational efficiency of reclaimers is critical for the overall performance of these terminals which are struggling with increasing workload. We study the variants of this problem with and without stacking operations. For each variant, we present a lower and an upper bound. A strong lower bound is obtained by relaxing the non-crossing constraint and solving the resulting problem to the optimality. While this relaxation still addresses a challenging scheduling problem, proposed arc-time-indexed formulation copes with the instances of practical size. We develop a novel constraint programming formulation to provide an upper bound for the problem. Computational experiments show this robust approach is able to generate near-optimal schedules for different stockyard configurations within a minute.