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Sustainability assessment with structural equation modeling in fresh food supply chain management
(Springer Heidelberg, 2021) Yontar, Emel; Ersöz, Süleyman
The aim of this study is to determine the dimensions that affect the sustainability performance of the fresh vegetable and fruit supply chain and to determine the performance that occurs along the chain line. In this study conducted for the fresh fruit and vegetable sector, it is desirable to measure each dimension by finding the performance indices of sustainable supply chain management. Dimensions of this study include supply chain management, resource management, food safety, packaging, and waste management. For these five dimensions gathered from the literature and expert opinions, 26 sub-criteria are determined for use in performance evaluation. Structural equation modeling (SEM) and analytical hierarchy process (AHP) methods are used together to calculate the performance index of each dimension and then to obtain a final fresh vegetable and fruit supply chain performance score. This study has been performed in Turkey. Turkey, between the countries of the world, is located in the top 5 in the fruit and vegetable production. The performance of the five different dimensions is calculated. In this performance assessment, supply chain management dimension is calculated as the highest performance with a score of 91.22%. The lowest performance index score as 66.77% is the waste management dimension. The final sustainable fresh fruit and vegetable supply chain performance score is calculated as 79.96%. In addition to the limited performance evaluation studies in the sustainable supply chain, the fact that this study deals with the food chain, modeling and creating a final performance demonstrates the innovative aspect of the study. Attention is also drawn to the parameters that need to be addressed for more sustainable food.
Shift scheduling solution with hybrid approach in a power plant
(Elsevier, 2021) Özder, Emir Hüseyin; Alakaş, Hacı Mehmet; Özcan, Evrencan; Eren, Tamer
This study focuses on staff scheduling problems in a natural gas combined cycle power plants with demanding shift systems. Scheduling the personnel working in power plants to the most suitable shift program can be arduous in terms of energy supply security. Natural gas combined cycle power plants are labor units where an expensive resource such as labor is used intensively. The primary aim in these types of enterprises is to ensure maximum employee satisfaction with min-imum operating and labor costs. To meet this goal, companies must use various techniques. Shift scheduling models can also be considered as one of the useful tools in this respect. A constraint pro-gramming model has been developed for the shift scheduling problem. This model allows personnel to be assigned equally to shifts, minimizing the cost increase due to overtime. The proposed model satisfies the need for electricity generation in a big natural gas combined cycle power plant was operated in Turkey with real data has an acceptable calculation time to obtain the optimal solution. Staff scheduling model with the proposed improvements to the problem is provided close to 33% compared with the present situation. The calculation results show that the constraint programming model gives better results than the current schedule. The specificity of this study can be listed as follows: Firstly; the different model is presented in detail for the personnel scheduling problem, compared with the actual results and the results of the proposed model. Secondly, the personnel scheduling problem is modelled as a task-source match with the standard scheduling logic and mod-elled effectively with constraint programming. With the model, suitable solutions can be produced in a short time calculation period. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
Single Machine Scheduling Problems With Time-Dependent Learning Effects
(Yildiz Technical Univ, 2013) Eren, Tamer
In traditional scheduling problems, most literature assumes that the processing time of a job is fixed. However, there are many situations where the processing time of a job depends on the starting time or the position of the job in a sequence. In such situations, the actual processing time of a job may be more or less than its normal processing time if it is scheduled later. This phenomenon is known as the learning effect''. In this study, we introduce a time-dependent learning effect into a single-machine scheduling problems. We consider the following objective functions: (i) maximum tardiness, (ii) number of tardy jobs (iii) maximum tardiness subject to the number of tardy jobs (iv) number of tardy jobs subject to maximum tardiness. A nonlinear programming model are developed for problems which belongs to NP-hard class. Also the model is tested on an example. According to the best of our knowledge, no works exists on the optimal solutions for four problems were examined.
Shortest Confidence Intervals of Weibull Modulus for Small Samples in Materials Reliability Analysis
(Gazi Univ, 2023) Yalçınkaya, Meryem; Birgören, Burak
The Weibull distribution has been widely used to model strength properties of brittle materials. Estimation of confidence intervals for Weibull shape parameter has been an important concern, since small sample sizes in materials science experiments bring about large intervals. Many methods have been proposed in the literature for constructing shorter intervals; the methods of maximum likelihood, least square, and Menon are among the most extensively studied methods. However, they all use an equal-tails approach. The pivotal quantities used for constructing confidence intervals have right-skewed and unimodal distributions, thus, they clearly do not produce the shortest intervals for a given confidence level in equal tail form. This study constructs the shortest confidence intervals for the three aforementioned methods and compares their performances by their equal-tails counterparts. To this end, a comprehensive simulation study has been conducted for the shape parameter values between 1 to 80 and the sample sizes between 3 to 20. The comparison criterion is chosen as the expected interval length. The results show that the shortest confidence intervals in each of three methods have yielded considerably narrower intervals. Further, the unknown parameter values are more centered in these intervals.
Sequential predictive maintenance and spare parts management with data mining methods: a case study in bus fleet
(Springer, 2024) İfraz, Metin; Ersöz, Süleyman; Aktepe, Adnan; Çetinyokuş, Tahsin
The sustainability of enterprises in an increasingly competitive environment is proportional to their ability to use the resources efficiently. Maintenance departments are critical to ensure that resources are ready and operational. Increasing the efficiency of maintenance departments depends on reducing the number of failures, performing planned maintenance on time and sustaining availability of spare parts needed. Therefore, it is vital that businesses consider predictive maintenance and spare parts jointly. In this study, predictive maintenance and spare parts integration studies are carried out using gearbox failure data and spare parts consumption data of a bus fleet. This study aims to contribute to the reduction of failure costs by finding failure patterns and predicting the subsequent failures and spare parts to be used. The sequential pattern mining approach was used to determine failure patterns and the traditional frequent itemset mining approach was used to predict spare parts. As a result, 45 failure patterns were found. Rules with a reliability of up to 79% were obtained. In addition, spare part clusters with a support value of approximately 40% were created. With this valuable information, businesses are able to investigate root causes, take precautions against future failures, make predictions about the spare parts that will be needed, and develop joint maintenance planning and inventory management policies.
Selection of wearable sensors for health and safety use in the constructıon industry
(Vilnius Gediminas Tech Univ, 2023) Aksut, Güler; Eren, Tamer
Construction industry workers; are exposed to serious safety and health risks, hazardous work environments, and intense physical work. This situation causes fatal and non-fatal accidents, reduces productivity, and causes a loss of money and time. Construction safety management can use wearable sensors to improve safety performance. Since there are many types of sensors and not all sensors can be used in construction applications, it is necessary to identify suitable and reliable sensors. This requirement causes a sensor selection problem. The study aims to determine the priority order of physiological and kinematic sensors in preventing risks in the construction industry. Within the scope of this purpose, five criteria and seven alternatives were determined in line with the literature research and expert opinions. The criteria weights were calculated with the AHP method, and the alternatives were ranked with PROMETHEE and AHP. Providing a proactive approach to the use of sensors in the construction industry will provide safer working conditions, identify work-ers at risk, and help identify and predict potential health and safety risks. It will contribute to the literature on improving construction health and safety management.
Selection of 3D printing technologies for prosthesis production with multi-criteria decision making methods
(Springer Heidelberg, 2024) Alakas, Hacı Mehmet; Yazıcı, Emre; Ebiri, Ufukcan; Kizilay, Berat Alperen; Oruç, Onur
Today, innovations are emerging in every field that comes with the constantly developing technology. 3D printers, among the developing technologies and making essential contributions, are significant in fields such as industry and health. 3D printers are used in many areas and provide various benefits, especially flexibility in production. 3D printers provide flexibility in producing products using multiple technologies according to the effect produced. However, differentiating the methods and alternatives creates an alternative selection problem for decision-makers. In this study, which is examined in this context, 3D printer technologies used in prosthesis production will be discussed. The study aims to find the most suitable prosthetic construction technology by comparing the 3D printer technologies used in prosthesis production to minimize the machine cost for prosthesis, eliminate mold production for personal prosthesis production, reduce production time, and customize. Five criteria were determined in selecting the 3D printer technology used in prosthesis production, and ten alternative technologies were listed according to the criteria. The criterion weights are calculated using the Analytical Hierarchy Process, a Multi-Criteria Decision-Making method-alternatives ranked by TOPSIS and PROMETHEE. The most suitable alternative was selected for prosthesis production. A decision-making procedure is proposed for decision-makers. The study demonstrates its originality by presenting analysis with multi-criteria decision-making methods to evaluate alternative 3D printers for prosthesis production.
Scheduling Two Parallel Machines with Sequence-dependent Setups and A Single Server
(Gazi Univ, 2011) Türker, A. Kürşad; Sel, Çağrı
This paper presents a scheduling problem on parallel machines with sequence-dependent setup times and setup operations that performed by a single server. The main purpose is to get minimum makespan of the schedule. The system is formulated as genetic algorithm with problem sizes consisting of two machines and 10, 20 and 30 jobs. A genetic algorithm is developed using random data sets. The optimum results are obtained using a string based permutation algorithm which scans all alternatives. As a result, proposed algorithm is effective to solve P2,S|STsd|Cmax scheduling problem on reasonable runtime and the results of the algorithm which are close to optimum solution values. Effectiveness of the solution is presented considering approximation rates of the genetic algorithm solutions to the optimum results obtained for P2,S|STsd|Cmax problem.
Scheduling and Rostering of Temporary Staff to Deal with Periodically Increasing Demand in Retail Sector: An Application
(Gazi Univ, 2022) Cürebal, Ahmet; Koçtepe, Serkan; Eren, Tamer; Özder, Emir Hüseyin
Temporary employment is a need to meet periodically increasing demand. It is arranged for a limited number of days and its service quality output is observed instantly. These make the planning phase complicated. In the process, the priority of businesses is to meet the increasing demand and to regulate the workload according to the terms of the period. Solving the periodic increase in demand by providing permanent employment can cause businesses to face the costs arising from excess employment in the long term. Generally, businesses manage these periods by hiring new staff. The most critical problems of the process are the suitability of the temporarily employed staff to work and whether they are suitable for the competencies in the job description. It is expected to achieve an efficiency equivalent to the cost to be incurred for this need that occurs in certain time periods. Adaptation processes, the effects of today's pandemic virus, and ergonomics issues owing to some tasks are the other basic constraints of this planning process. In this study, the problem of scheduling and rostering of staff requested for the problem of staff shortage owing to periodically increased demand has been solved. 50 candidate staff were evaluated in 4 competency types. Thus, an optimized service quality and staff costs has been achieved for this periodic staff need. For problem solving, 0-1 integer programming model was established and the proposed model, is written in ILOG CPLEX Studio IDE and is solved with the CPLEX solvent.
Ranking of sectors in organized industrial zones according to Natech risk criteria: An application for Gaziantep province in Türkiye
(Elsevier Sci Ltd, 2024) Güven, Emel; Pınarbaşı, Mehmet; Alakaş, Hacı Mehmet; Eren, Tamer
Technological accidents triggered by natural disasters are called Natech accidents. Natech accidents have the impact of increasing the negative effects of disasters. One of the places at risk for a Natech accident is the Organized Industrial Zones (OIZs), where many industrial establishments are located. Although businesses within OIZs are evaluated in terms of security, Natech risk assessment is often ignored. This situation causes Natech accidents to occur. For these reasons, the study focused on evaluating OIZs regarding Natech risk. Many criteria such as electrical resources, natural gas, distance between buildings and so forth are taken into account in Natech's risk assessment. However, it is challenging to make clear decisions and predictions about these criteria due to the nature of the disaster. There is inherently uncertainty and confusion during and after a disaster. For this reason, using fuzzy sets to evaluate criteria is more appropriate. Therefore, the study uses Pythagorean fuzzy sets, which have a wider fuzzy evaluation area. This study also includes the evaluation of alternative sectors in terms of Natech risk. For this purpose, Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) and Pythagorean Fuzzy the Technique for Order of Preference by Similarity to Ideal Solution (PFTOPSIS) methods are used. OIZ in Gaziantep has the largest area compared to those in other cities in T & uuml;rkiye, is chosen as the application area of the study. As a result of the study, it is determined that the release of hazardous substances and flammable criteria is the most crucial criterion, and the most dangerous sector in terms of Natech risk is the chemical sector.
Ranking of advertising goals on social network sites by Pythagorean fuzzy hierarchical decision making: Facebook
(Pergamon-Elsevier Science Ltd, 2023) Bulut, Merve; Özcan, Evrencan
The rapid growth of social networking sites (SNSs), known as web-based services, has become a natural digital phenomenon, reinforcing e-commerce concepts such as business-to-consumer (B2C) and consumer-to-consumer (C2C), known as social commerce. One platform that provides end-to-end connections, from increasing brand awareness to creating new opportunities in the contemporary marketing approach, is Facebook, which reaches a broad audience of advertisers with the advantage of many users. Facebook has updated its ad targets in recent years. Choosing the right advertising target will directly affect company and campaign performance. Considering this problem structure, it is compatible with fuzzy set theory since it contains conflicting criteria and high complexity in an environment of uncertainty. As far as it is known from the literature, although there are many academic studies on Facebook ad analysis, there is no study investigating advertising targeting with fuzzy set theory. Therefore, in the decision model developed for Facebook advertising targeting, a fuzzy decision model is proposed for targeting by the campaign structure. The first stage of the model includes the combined use of AHP-TOPSIS methods by evaluating performance criteria and presenting advertising targets in social media campaigns with Pythagorean fuzzy sets. As a result, it has been reached that the awareness-raising strategy for local or global users should include campaign activities that will increase brand awareness.
Railway security personnel scheduling problem considering personnel preferences
(Springer, 2024) Gencer, Muhammed Abdullah; Alakas, Hacı Mehmet; Pınarbaşı, Mehmet; Eren, Tamer
This study discusses the shift scheduling problem of security personnel, considering personnel preferences for 43 stations on four lines of the Ankara metro, which carries more than 10 million passengers monthly. Firstly, 751 security personnel have been distributed to four lines of the Ankara metro according to personnel needs. A survey is conducted among the personnel at the stations on each line, and they are asked to rank the stations they want to work at according to their preferences. The station preferences of the personnel are listed with increasing scoring in parallel with the order of preference. A goal programming model has been used to assign personnel to stations, considering personnel needs, operating rules, and personnel preference scoring at the stations. The main objective of the model is to minimize the personnel-preferred station scoring. As a result of the solution of the mathematical model solved separately for four lines, 24.23% of the personnel for the M1 (K & imath;z & imath;lay-Bat & imath;kent) line, 27.94% of the personnel for the M2 (K & imath;z & imath;lay-Koru) line, 23.32% of the personnel for the M3 (Bat & imath;kent-Sincan) line, and 35.85% of the personnel for the M4 (Ke & ccedil;i & ouml;ren-& Scedil;ehitler) line, are assigned to their first three preferences. Moreover, an important balance is achieved between personnel preferences. Few studies are in the literature on railway security personnel scheduling, and no studies that consider personnel preferences have been found in this field. This study, which considers personnel preferences, contributes to the literature.
Prioritizing of sectors for establishing a sustainable industrial symbiosis network with Pythagorean fuzzy AHP- Pythagorean fuzzy TOPSIS method: a case of industrial park in Ankara
(Springer Heidelberg, 2023) Yazıcı, Emre; Alakaş, Hacı Mehmet; Eren, Tamer
Difficulty in accessing resources and increasing environmental concerns encourage industrial manufacturing enterprises to establish a symbiosis network. The identification of symbiotic relationships contributes to the more sustainable development of industrial activities. However, businesses operating in industrial parks are diversified by sector. In order to establish a sustainable symbiosis network in industrial parks, the symbiotic relations of each sector in industrial parks should be evaluated separately. Thus, the installation process of the symbiosis network will be easier and more sustainable. In this context, this study aims to prioritize the sector in which a symbiosis network will be established by presenting an innovative approach for the evaluation of symbiosis potentials. For this purpose, criteria for the implementation process affecting the establishment of the symbiosis network were determined. Multi-criteria decision-making methods were used to solve the problem. Considering the uncertainties in the process, fuzzy multi-criteria decision-making methods were used. As a result, a decision-making model has been proposed to determine the priority sector in order to establish a symbiosis network in industrial parks. According to the results obtained with the multi-criteria decision-making methods, the number of enterprises that will evaluate the waste, that is, the number of customers with waste, has been determined as the criterion with the highest level of importance. While evaluating the alternatives, the casting sector was chosen as a priority. This sector is followed by the petro and chemical sector as the second alternative.
Prioritizing Individuals Who Will Have Covid-19 Vaccine with Multi-Criteria Decision Making Methods
(Gazi Univ, 2023) Yazıcı, Emre; Üner, Sabire İrem; Demir, Asli; Dinler, Sevda; Alakaş, Hacı Mehmet
This study aims to prioritize individuals in vaccination for the effective use of the COVID-19 vaccine, which has limited supply and does not seem possible to be supplied by all countries at the same time. In the study, multi-criteria decision-making methods (MCDM), which offer practical solutions to decision problems, were used considering the structure of the problem. First, the analytic hierarchy process (AHP) method was used to calculate the weights of the criteria. Then, the ranking of the priorities of the individuals was carried out with the PROMETHEE method. Here, the AHP and PROMETHEE methods are used in an integrated manner. It has been determined that the highest priority individual in vaccination is a healthcare worker with a high potential for transmission. In order of priority, the second individual was identified as workers. In this study, a hierarchical structure was created to prioritize individuals who will be vaccinated against COVID-19 and the problem was solved in two stages. A health policy proposal was made to health managers to use limited vaccine resources by prioritizing individuals effectively. In terms of efficient and effective use of resources during possible pandemic periods, the application process of the study provides an exemplary solution for decision-makers and contributes to the solution of similar decision problems encountered both in the literature and in real life. At the same time, offers solution for disasters that require effective use of limited resources, etc. The implementation process of the study may also be taken into account in exceptional circumstances.
Balancing of cost-oriented U-type general resource-constrained assembly line: new constraint programming models
(Springer, 2023) Alakaş, Hacı Mehmet; Pınarbaşı, Mehmet
In simple assembly line balancing problems, it is assumed that the resources required to perform the tasks are available at the relevant station for task assignment. However, each task may need different resource types depending on the difficulty, complexity and technical requirements of the tasks in real life. For this reason, tasks and resources belonging to these tasks must be assigned to the relevant station while balancing the line. In this study, the resource-constrained U-shaped assembly line balancing problem (U-GRCALBP) is discussed. According to the literature research, there is no study dealing with U-GRCALBP. Two different constraint programming (CP) models that define the resource constraints as and/or constraint types with concurrent resource types have been developed. In these models, the sum of resource usage costs and station opening cost minimization is aimed. The models are explained with an illustrative example and the efficiency of the models is tested by deriving new resource constraints on five different data set each taking into account four different cycle times and the number of two and four resource types. The number of stations obtained, the total number of resources used, total station opening and resource usage costs, and CPU time are used as performance criteria The results are compared with the traditional U-type assembly line balancing problem results. The proposed CP models give superior performance on all data sets, especially in terms of total cost. The numerical results show that both CP models are effective in solving the problem. Furthermore, some managerial implications are presented to be useful for professionals, organizations, and society.
Assembly line balancing type-1 problem with assignment restrictions: A constraint programming modeling approach
(Pamukkale Univ, 2021) Pınarbaşı, Mehmet; Alakas, Haci Mehmet
The assembly line balancing problem (ALBP) contains some constraints which are cycle time/number of stations and precedence relations between tasks. However, due to the technological and organizational limitations, several other restrictions, such as linked tasks, incompatible tasks, station, and resource constraints, can be encountered in real production systems. In this study, we evaluate the effect of these restrictions on ALBP. For this purpose, a Constraint Programming (CP) model is proposed. The objective of the model is to minimize the number of stations for given cycle time (Type-1 problem). We investigate the solution quality of the proposed CP model according to the mixed-integer programming (MIP) and ABSALOM in terms of the several performance measurements such as the number of proofing optimal solution, number of the optimal solution, number of the best solution, relative gap between the solution with the optimal solution and average total solution time. Furthermore, the proposed approach is tested on the literature test instances, and the comparison results between models are reported. Although assignment restrictions increase the complexity of the problem, numerical experiments demonstrate that CP is an effective and high-quality solution method in solving ALBP.
Applications Of The Moora And Topsis Methods For Decision Of Electric Vehicles In Public Transportation Technology
(Vilnius Gediminas Tech Univ, 2022) Hamurcu, Mustafa; Eren, Tamer
The technological development of buses among the new alternative concepts is evaluated in this paper. Bus transportation is an important system in the public transportation, which is cheap, flexible and, in many cases, in terms of capacity and speed. But increasing car traffic in the city centre and increasing the emission such as Carbon Dioxide (CO2) in the air are some of the dangerous problems for urban life. Therefore, it is needed the public transportation to stop in-creasing car traffic and needed the cleaner technology for air and environmental quality. Electric Buses (EBs) can play an important role for resident's life quality with improving the urban air quality. However, planners and managers have dif-ficulty in decision-making due to diversified EBs together with the developing technology. Multi-criteria decision-making (MCDM) methods that are analytic decision processes, prepare a good solution for this problem. In this study, 5 EBs are assessed under the special criteria with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization on the basis of the Ratio Analysis (MOORA) methods. These 2 methods are MCDM meth-ods that are used to aim of ranking of alternatives in the complex decision problem. These methods are applied to select the best EB under the 6 criteria. Finally, E5-Bus is selected as the best option that rank of the 1st at all the 3 methods. Besides, MOORA and TOPSIS methods were compared. The results are shown alongside the best bus selection for public transportation that MOORA method is also a strong tool for solving vehicle selection problems in transportation. The proposed model has been validated using existing real applications. The proposed multi-criteria analysis can be used for advising decision-makers in their decision-making process for Electric Vehicles (EVs) in the area of clean transportation.
Analytic network process and TOPSIS methods with selection of optimal investment strategy
(Yildiz Technical Univ, 2013) Görgülü, İnci; Korkmaz, Melek; Eren, Tamer
In this paper, optimal investment strategy selection problem is handled, that is very important for companies, and a analytic network process (ANP) and technique for order preference by similarity to an ideal solution (TOPSIS) based approach is proposed to solve this selection problem. ANP method is used to determine the importance degree of main criteria and subcriteria, TOPSIS method is developed to rank the alternatives. A silver firm's data were analyzed to select optimal investment strategy.
Analysis of operations research methods for decision problems in the industrial symbiosis: a literature review
(Springer Heidelberg, 2022) Yazıcı, Emre; Alakaş, Hacı Mehmet; Eren, Tamer
Industrial symbiosis (IS) is an approach that aims to use resources efficiently by cooperating between independent enterprises in raw materials, energy, and similar sectors. As a result of cooperation, businesses gain economic, environmental, and social benefits. Especially in recent years, IS applications have become widespread due to the problems experienced in the supply of resources. The presence of more than one enterprise in cooperation creates a complex network structure in IS applications. In this complex system, many decision problems are encountered in establishing and effectively maintaining the industrial symbiosis network. Operations research techniques are at the forefront of the methods used to solve decision problems. This study examined studies using operations research techniques in industrial symbiosis. Studies were divided into four classes according to the methods they used: exact methods, heuristic methods, multi-criteria decision-making, and simulation. In the literature review, the studies in the Web of Science (WOS) database are systematically presented by scanning with the determined keywords. As a result of the study, it was analyzed which method was preferred and where the methods could be applied in industrial symbiosis.
Analysis of factors affecting industrial symbiosis collaboration
(Springer Heidelberg, 2022) Sonel, Edanur; Gür, Şeyda; Eren, Tamer
The rapidly increasing population causes an increase in consumption amounts day by day. This leads to negative effects such as the reduction of limited resources. In order to eliminate or reduce such negative effects, sustainable approaches are adopted for the future. Industrial symbiosis is one of these sustainable approaches. Industrial symbiosis is when two or more economic enterprises operating independently of each other form beneficial partnerships. In this study, the factors affecting industrial symbiosis collaboration were determined by literature review and by analyzing these factors; it is aimed to eliminate inefficiencies and to ensure the sustainability of established relations. The criteria determined are weighted with the Analytical Network Process method, which is one of the multi-criteria decision-making methods, and it is aimed to calculate the degree of importance and priority.

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