Yazar "Göçmen, Elifcan" seçeneğine göre listele

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    A Tabu Search Algorithm for an Excavator Scheduling Problem
    (Umut SARAY, 2020) Göçmen, Elifcan; Derse, Onur
    Global sector prompts the construction firms to give a priority to time and cost factors. Thus, scheduling of the jobs is focal important to achieve cost and time objectives. Scheduling problems have gained a great importance in recent years in the construction sector. We have examined a single machine scheduling problem for an excavator used in the construction sector. There are some jobs in which each job has a normal processing time, a due date, earliness penalty and tardiness penalty. This paper presents a meta-heuristic optimization algorithm named Tabu Search (TS) to minimize the total cost and provides how it can be used to solve a wide variety of single machine scheduling problems. Computational results demonstrates that the proposed approach is a good tool for these problems.
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    An Optimization Approach for A Biogas Supply Chain using Goal Programming and Mixed Integer Linear Programming
    (2023) Derse, Onur; Göçmen, Elifcan
    Environmental concerns prompt the world for a transition to renewable energy sources from fossil energy. Reducing the dependency on non-renewable sources of energy is prerequisite for the sustainable world and less environmental pollution. Biogas energy, which is one of the most important renewable energy sources, is produced by burning organic wastes and can be used in many different fields. In this study, a two-stage approach is undertaken to optimize a biogas supply chain design by incorporating of 30 districts in Izmir. In the first stage, the selection of the most suitable biogas plants is considered by the goal programming approach, which is of great importance to decide the optimal location with high energy potential. The most suitable sites for the biogas plants are obtained as Konak and Narlıdere districts. In the second stage, the location problem of the biogas vehicle charging stations (BVS) for biogas vehicles is handled considering the results of the first stage using mixed integer linear programming (MILP) approach. Computational results demonstrate that it would be more appropriate to establish BVS in 12 districts of İzmir. The model and solution approach are pioneering for supply chain problems and an efficient tool for renewable energy plans.
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    RISK ASSESSMENT USING A NOVEL HYBRID METHOD: A CASE STUDY AT THE BIOCHEMISTRY DEPARTMENT
    (2021) Narli, Mufide; Göçmen, Elifcan; Derse, Onur
    Risk management has gained substantial attention for the health sector in recent years. Healthcare systems are forced to deal with risk assessment due to deadly accidents. Biochemistry department is one of the most critical units, in which occupational accidents should be controlled preventively. Thus, this paper aims at developing a risk assessment process to minimize the occupational accidents. Failure mode and effects analysis (FMEA) and 5x5 matrix (L Matrix) as most effective quantitative risk analysis methods, are developed for a biochemistry department of a hospital in Turkey to evaluate the risk types discussed in related works and discovered during this work. First, the decision makers’ risk evaluation based on historical data of accidents are adopted to risk management process. Then, with regard to scoring of risk factors such as occurrence, severity and detectability, risk priority numbers and classes are obtained and preventive measures for the high-risk failure modes are determined. Analytic Hierarchy Process (AHP) method has been applied for prioritizing these measures to reduce or eliminate these risk types. Considering the results obtained from the AHP method, a goal programming model is developed to minimize the risk prevention costs. Obtained results demonstrate the effectiveness of the proposed methods.