Ceyhun Araz

An integrated multicriteria decision-making methodology for outsourcing management

In this study, an outsourcer evaluation and management system is developed for a textile company by use of fuzzy goal programming (FGP). At first phase of the methodology, evaluation criteria for the outsourcers and the objectives of the company are determined. The existing outsourcers of the company are evaluated by PROMETHEE. At the second phase, the FGP model developed selects the most appropriate outsourcers suitable to be strategic partners with the company and simultaneously allocates the quantities to be ordered to them. In the end, the results achieved are compared with the current situation of the company. The results indicated that scientific methodology for outsourcer management system is very beneficial for the company. Scope and purpose The purchasing activities of a company constitute a very important part in the overall operation of the company. The quality and the delivery capabilities of any manufacturing firm depend heavily on the performance of its suppliers. When companies outsource a significant part of their business and become more dependent on outsourcers, the quality and delivery performance of the company depends totally on its outsourcers. The consequences of poor decision making become more severe. It is therefore too important for an outsourcing type manufacturer to evaluate, manage and select their suppliers. This research proposes an outsourcer evaluation and management system on scientific basis. The procedure developed is made up of two phases. The first one is the evaluation of outsourcers in terms of the decision makers objectives. This phase is followed by FGP modeling phase which provides the decision maker the list of suitable outsourcers.

A fuzzy multi-objective covering-based vehicle location model for emergency services

Abstract Timeliness is one of the most important objectives that reflect the quality of emergency services such as ambulance and firefighting systems. To provide timeliness, system administrators may increase the number of service vehicles available. Unfortunately, increasing the number of vehicles is generally impossible due to capital constraints. In such a case, the efficient deployment of emergency service vehicles becomes a crucial issue. In this paper, a multi-objective covering-based emergency vehicle location model is proposed. The objectives considered in the model are maximization of the population covered by one vehicle, maximization of the population with backup coverage and increasing the service level by minimizing the total travel distance from locations at a distance bigger than a prespecified distance standard for all zones. Model applications with different solution approaches such as lexicographic linear programming and fuzzy goal programming (FGP) are provided through numerical illustrations to demonstrate the applicability of the model. Numerical results indicate that the model generates satisfactory solutions at an acceptable achievement level of desired goals. Scope and purpose This paper considers the emergency service vehicles location problem. A multi-objective maximal covering location model is proposed in this paper. The model addresses the issue of determining the best base locations for a limited number of vehicles so that the service level objectives are optimized. Three of the important surrogates that reflect the quality of emergency service systems are considered as objectives in the model: maximization of the population covered by one vehicle, maximization of the population with backup coverage and minimization of the total travel distance from locations at a distance bigger than a prespecified distance standard for all zones. The proposed model allows the incorporation of decision makers imprecise aspiration levels for the goals by means of FGP approach. Thus, the solution efficiency inherent in the FGP approaches is also included into the model. To demonstrate the applicability of the model, numerical examples are provided using different solution approaches.

A Multicriteria Decision Aid Approach on Navel Selection Problem for Rotor Spinning

In studies about optimization of rotor spinning machine parameters, generally classical statistical methods have been used; the priorities and preferences of the yarn producer about yarn properties to get the desired end product characteristics have not been taken into consideration. However, machine part selection from possible alternatives with different properties and performance levels about yarn quality is a difficult task and inherently a multicriteria decision-making problem. In this study, it is proved that application of a multicriteria decision aid method, ELECTRE III, can provide valuable assistance in reaching acceptable solutions in order to select the appropriate navel for Ne 12 rotor yarn spun to weave denim fabric. In experimental part of the study, Ne 12 rotor yarns were spun by using ten navels having different technical properties and their quality parameters were analysed with ELECTRE III.

A multicriteria sorting procedure for financial classification problems: the case of business failure risk assessment

This paper presents a new multicriteria sorting procedure in financial classification problems, based on the methodological framework of PROMETHEE method. The proposed procedure, called as PROMSORT, is applied to the business failure risk problem and compared to PROMETHEE TRI and ELECTRE TRI. The proposed methodology also identifies the differences in performances across risk groups, and assists in monitoring the firms’ financial performances. The results showed that the proposed procedure can be considered as an effective alternative to existing methods in financial classification problems.

AN INTEGRATED FUZZY APPROACH FOR DETERMINING ENGINEERING CHARACTERISTICS IN CONCRETE INDUSTRY

This paper deals with the modeling of conceptual knowledge to capture the major customer requirements effectively and to transform these requirements systematically into the relevant design requirements. Quality Function Deployment (QFD) is a well-known planning and problem-solving tool for translating customer needs (CNs) into the engineering characteristics (ECs) and can be employed for this modeling. In this study, an integrated methodology is presented to rank ECs for implementing QFD in a fuzzy environment. The proposed methodology uses fuzzy weighted average method as a fuzzy group decision making approach to fuse multiple preference rankings for determining the weights of the customer needs. It adopts a fuzzy Analytic Network Process (ANP) approach which enables the consideration of inner dependencies in a cluster as well as the interdependencies between the clusters to determine the importance of ECs. The proposed approach is illustrated through a case study in ready-mixed concrete industry.

Lagrangian-Based Solution Approaches for a Resource-Constrained Parallel Machine Scheduling Problem with Machine Eligibility Restrictions

This study is motivated by a real world scheduling problem in an injection molding department of an electrical appliance company. In this paper, a resource-constrained parallel machine scheduling problem with machine eligibility restrictions is investigated. For the problem, an integer linear program is developed with the objective of minimizing total flow time. Based on this model, a Lagrangian-based solution approach with a subgradient optimization procedure has been proposed. Additionally, a problem-specific heuristic algorithm is developed to obtain near-optimal solutions. Through randomly generated instances of the problem, it is demonstrated that the proposed algorithms generate not only very tight lower bounds but also efficient results with a small optimality gap.

Disassembly line balancing using linear physical programming

Disassembly is the separation of a product into its constituent parts in a systematic way. It has gained importance recently due to its vital importance in product recovery. Cost-effective implementation of disassembly operation has a direct impact on the profitability of product recovery activities (recycling, remanufacturing etc.). Although it is possible to carry out disassembly operations in a disassembly station or in a disassembly cell, the highest productivity is achieved in a disassembly line. The output of a disassembly line can be maximised only if the line is balanced. A linear physical programming-based disassembly line balancing method is proposed in this study. This method was used to balance a mixed-model disassembly line and the effectiveness of the method was illustrated by analysing the results.

A multi-criteria decision making procedure based on neural networks for kanban allocation

In this study, we proposed a methodology for determining optimal number of kanbans for each station in a JIT manufacturing system. In this methodology, a backpropagation neural network is used in order to generate simulation meta-models, and a multi-criteria decision making technique (TOPSIS) is employed in order to evaluate kanban combinations with respect to the relative importance of the performance measures. The proposed methodology is applied to a case problem and the results are presented. The results show that the methodology can solve this type of problems effectively and efficiently.

A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT

Abstract Depleting natural resources and limited amount of landfill areas have forced many governments to impose stricter measures on environmental performance. In order to comply with those measures and to have a better environmental image, companies are investing heavily in environmental, social and economic responsibility issues. Moreover, they continuously track the environmental performance of their suppliers. Many green supplier evaluation and ranking methodologies were proposed in the literature in order to assist companies in the environmental performance evaluation of suppliers. However, the number of studies on the sorting of suppliers based on environmental criteria is very limited. In this study, we fill this research gap by proposing a novel VIKOR-based green supplier sorting methodology called VIKORSORT. This methodology evaluates the environmental performance of suppliers and sorts them into the predefined ordered classes. The proposed methodology can easily be embedded into an expert system which can suggest a suitable green supplier development program for each class.

RADYO FREKANS TANIMLAMA SİSTEMİNE DAYALI HAMMADDE DEPO YÖNETİMİ - RFID BASED RAW MATERIAL WAREHOUSE MANAGEMENT

FERMENTE ET URUNLERINDE PROBIYOTIK MIKROORGANIZMALARIN KULLANIMI Probiyotik gidalar, son yillarda genis olcude ticari ilgi goren, pazar payi gittikce buyuyen ve insan sagligi uzerinde olumlu etkilere sahip fonksiyonel gidalardir. Probiyotik mikroorganizmalarin insan vucudunda aktif hale gecebilmesi icin gastrointestinal sisteme bir tasiyici araciligiyla ulasmasi gerekmektedir. Bu tasiyici genellikle canli probiyotik bakterileri iceren bir besindir. Probiyotik gidalarin raf omru uzun olmali ve bunyesinde en az 106 kob/g canli mikroorganizma icermelidir. En yaygin kullanilan probiyotik mikroorganizmalar, Lactobacillus, Bifidobacterium ve Streptococcus cinslerine ait turlerdir. Et, probiyotikler icin mukemmel bir aracidir. Probiyotiklerin fermente urunler icerisinde canliligini surdurebilmesi, pH, asitlik, molekuler oksijen, hidrojen peroksit, bakteriyosin ve farkli katki maddelerinin varligi ile mikrobiyal rekabete baglidir. USING PROBIOTIC MICROORGANISMS IN FERMENTED MEAT PRODUCTS Probiotic foods are functional foods which have wide range comercial interest, growing market and positive effects on human health in recent years. Probiotic organisms become active in the human body, these organisms must be reach to the gastrointestinal system via a vehicle. This vehicle is a food which contains probiotic bacteria. Probiotic foods should have a long shelf life and contains at least 106 cfu / g live micro-organisms. The most commonly used probiotic microorganisms are Lactobacillus, Bifidobacterium and Streptococcus species of genus. Meat is an excellent tool for probiotics. Maintain viability of probiotics in fermented products associated with pH, acidity, molecular oxygen, hydrogen peroxide, bacteriocins, microbial competition and the presence of different additives.