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    A green model for the catering industry under demand uncertainty
    (Elsevier Sci Ltd, 2017) Sel, Cagri; Soysal, Mehmet; Cimen, Mustafa
    In this study, we design a catering supply chain involving production and service management. The production management involves food production lot-sizing and delivery scheduling decisions, while the service management is associated with balancing the food service lines. If production is in excess of demand, the food waste occurs along the catering chain. If the quantity produced is less than demand, this leads to a shortage. To address this problem, we develop a stochastic programming model accounting for the key performance indicators of total waste, total shortage and total cost of production and distribution. The selected indicators enable to assess the sustainability performance of the catering supply chain. The numerical study reflects real settings from catering operations of a university cafeteria in Turkey. For a sustainable development of catering supply chains, the analyses reveal the potential benefits of outsourcing (e.g., decreasing total costs by 36% and waste costs by 23%), employing qualified staff and increasing capacity through process improvement. (C) 2017 Elsevier Ltd. All rights reserved.
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    A heuristic approach for green vehicle routing
    (Edp Sciences S A, 2021) Soysal, Mehmet; Cimen, Mustafa; Sel, Cagri; Belbag, Sedat
    This paper addresses a green capacitated vehicle routing problem that accounts for transportation emissions. A Dynamic Programming approach has been used to formulate the problem. Although small-sized problems can be solved by Dynamic Programming, this approach is infeasible for larger problems due to the curse of dimensionality. Therefore, we propose a Dynamic Programming based solution approach that involves the ideas of restriction, simulation and online control of parameters to solve large-sized problems. The added values of the proposed decision support tool have been shown on a small-sized base case and relatively larger problems. Performance comparisons of the proposed heuristic against other existing Dynamic Programming based solution approaches reveal its effectiveness, as in most of the instance-setting pairs, the proposed heuristic outperforms the existing ones. Accordingly, the proposed heuristic can be used as an alternative decision support tool to tackle real routing problems confronted in sustainable logistics management.
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    INVIGILATORS ASSIGNMENT IN PRACTICAL EXAMINATION TIMETABLING PROBLEMS
    (Univ Cincinnati Industrial Engineering, 2022) Cimen, Mustafa; Belbag, Sedat; Soysal, Mehmet; Sel, Cagri
    This paper addresses an invigilator assignment problem. The problem deals with a set of exams, each of which requires a given number of invigilators. The aim is to prepare a conflict-free schedule where all invigilator requirements of the exams are met. In this study, the conflict-free schedule is determined by a mixed-integer linear programming model and a heuristic algorithm that accounts for the following real-life concerns; assignment of the invigilators responsible for an exam, reduction of the number of successive invigilation duties, fair distribution of total workload and unfavorable workload among invigilators and, prioritization of the assignments based on invigilators??? profession. The applicability of the proposed model and the heuristic algorithm has been shown on eight different real-life problems of leading public universities in Turkey and further eight larger-sized examinations set up based on the real settings. In universities, the real schedules are manually prepared by a faculty team. Compared to the assignment of the faculty team responsible for the examination of timetabling in which balancing only the numbers of duties, we achieved to 86% decrease in the total positive error of invigilation hours by fairly distributing the invigilation duties in the model results. Besides, the following improvements are achieved by applying the proposed model; a 56% decrease in the total number of successor assignments, a 44% decrease in the total unfavorable time, and a 23% increase in the total number of department-based assignments. The heuristic algorithm improves the team schedules by 4% in terms of the total positive error of total invigilation hours and 57% in terms of the total number of successive exam assignments. Accordingly, the proposed model and the heuristic algorithm can be used as a decision support tool by the faculty team.
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    Modeling a closed-loop inventory routing problem for returnable transport items under horizontal logistics collaborations and dynamic demand structure
    (Taylor & Francis Ltd, 2024) Yavrucu, Erencan; Soysal, Mehmet; Sel, Cagri; Cimen, Mustafa; Hamzadayi, Alper
    This paper addresses a closed-loop inventory routing problem with multiple suppliers, products, and periods under horizontal collaboration assumptions. Our problem encompasses various decision aspects, including routing, inventory management, product delivery, returnable transport item collection and cleaning. We analyze various logistics collaboration scenarios. The effects of demand dynamicity are also assessed. The problem has been mathematically defined as a Mixed Integer Linear Programming model. A rolling horizon approach and a hybrid heuristic algorithm are proposed for instances that exceed the computational requirements of solving the exact MILP model. The applicability and potential benefits of the MILP model and the proposed solution methodologies are demonstrated through a base case and additional numerical analyses on larger-sized instances and networks. The results show that supplier collaboration significantly reduces routing costs, while customer collaboration reduces inventory costs. Numerical comparisons reveal that the proposed algorithms outperform the MILP model for large-scale problem instances.