Huseyin Basligil

An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection

Previous methods for enterprise software selection generally take into account the attributes that are restricted to some financial factors, such as costs and benefits. However, the literature lacks studies on considering the evaluation of both functional and non-functional suitability of software alternatives versus various requirements. This study presents a new decision support system for combining these two kinds of evaluation to select suitable enterprise software. A hierarchical objective structure that contains both qualitative and quantitative objectives is proposed to evaluate software products systematically. This approach uses a heuristic algorithm, a fuzzy multi-criteria decision making procedure and a multiobjective programming model to make final selection decision. All the phases of presented method are applied in an electronic companys ERP software selection project to validate it with a real application. The satisfactory results are obtained during this project. The company can select the right software to fit its business processes instead of adapting its business processes to fit the software.

A framework for defining both qualitative and quantitative supplier selection criteria considering the buyer–supplier integration strategies

Previous research has reported that the decision criteria used to evaluate suppliers differ by product category. This paper presents a framework for defining the supplier selection criteria by investigating possible quantitative and qualitative criteria reported by earlier studies according to the levels of buyer–supplier relationship, the companys competitive situation and its corporate strategies, rather than investigating these criteria in respect of product category. The solution proposed in this study not only assists decision makers to define selection criteria, but also supports determining the buyer–supplier integration level. An actual case in Audio Electronics, a Turkish electronics business, demonstrates the feasibility of applying the proposed framework in practice.

Pre-selection of suppliers through an integrated fuzzy analytic hierarchy process and max-min methodology

There are a variety of analytical models for supplier selection ranging from simple weighted techniques to complex mathematical programming approaches. However, these models are specifically aimed at supporting a decision maker in a single phase, especially in the final selection phase and they have failed to consider the supplier selection process from a holistic point of view. Although the methodology presented in this paper primarily focused on the prequalification of potential suppliers, the outputs of the previous phases, namely problem definition and formulation of criteria, are used as inputs in this methodology. The methodology utilises a fuzzy analytic hierarchy process (AHP) method to determine the weights of the pre-selected decision criteria, a max-min approach to maximise and minimise the supplier performances against these weighted criteria, and a non-parametric statistical test to identify an effective supplier set. This information supports decision makers in making the final selection with effective alternative choices. Potential application of the proposed methodology is demonstrated in Audio Electronics in Turkeys electronics industry.

Modelling product-recovery processes in closed-loop supply-chain network design

Recent changes in environmental requirements have forced manufacturing operations to face a new challenge, which is to develop green strategies to design supply chains and their processes. This study describes the specific features of green supply-chain design considering end-of-life products. We propose a mixed integer linear programming model to obtain the optimal closed-loop supply-chain (CLSC) network design, in which recovery process occurs in three different ways: material recovery, component recovery, and product recovery. An extensive analysis is supported by numerical results which inform CLSC managers about the opportunities of enhancing product returns in terms of quality and quantity. To define a better CLSC strategy to increase system profitability, the volume of product returns and corresponding quality conditions should be considered in the design of a CLSC network. The numerical study provides information for us to discuss the potential benefits of product-recovery processes and the reaction of system profitability to the changes in specific CLSC parameters.

A weakness determination and analysis model for business process improvement

Purpose – Modeling of the methods for providing improvements in business processes by value adding is researched with an integrated approach. The main purpose in this approach is improving the processes by determining and analyzing the weak points and reducing the weakness degrees.Design/methodology/approach – The designed model determines weak points that need to be improved, analyzes them to find privileged processes in improvement by considering improvement costs and obtains the improvement degrees for defining the improvement strategy by four‐phase business process improvement framework: start‐up, self analysis, defining improvement strategy for making changes, feedback, and continuous improvement.Findings – The key factor in keeping up with changes in market conditions is systematic application of improvement efforts and providing planned and controlled value addition with these improvements. Decision problems in process improvement can be structured to provide input data suitable for multi‐criteria ...

A genetic algorithm application using fuzzy processing times in non-identical parallel machine scheduling problem

There are many scheduling problems which are NP-hard in the literature. Several heuristics and dispatching rules are proposed to solve such hard combinatorial optimization problems. Genetic algorithms (GA) have shown great advantages in solving the combinatorial optimization problems in view of its characteristic that has high efficiency and that is fit for practical application [1]. Two different scale numerical examples demonstrate the genetic algorithm proposed is efficient and fit for larger scale identical parallel machine scheduling problem for minimizing the makespan. But, even though it is a common problem in the industry, only a small number of studies deal with non-identical parallel machines. In this article, a kind of genetic algorithm based on machine code for minimizing the processing times in non-identical machine scheduling problem is presented. Also triangular fuzzy processing times are used in order to adapt the GA to non-identical parallel machine scheduling problem in the paper. Fuzzy systems are excellent tools for representing heuristic, commonsense rules. That is why we try to use fuzzy systems in this study.

A distribution network optimization problem for third party logistics service providers

Third party logistics service providers (3PLs) have an important role in supply chain management. Increasing cooperation with 3PLs is expanding in todays business environment. Hence, 3PLs need to have an efficient distribution network to meet customer demands. Nevertheless, few researches have tried to propose a solution for distribution network problems of 3PLs. The optimization problem which is discussing in our study is solved in two stages. At the first stage, the assignment problem which includes assigning the order of the vehicles is solved with mixed integer programming by using GAMS 21.6/CPLEX. The output of the first stage is used as an input in the second stage. In this stage routes are determined for vehicles by developing a genetic algorithm by using C#.

A combined DEMATEL and grey system theory approach for analyzing occupational risks: A case study in Turkish shipbuilding industry

ABSTRACT The shipbuilding industry is known as heavy industry because of its high-risk work activities. Therefore, in order to prevent fatal occupational accidents in the shipbuilding industry, the processes of defining hazards, evaluating risks, taking action to eliminate or reduce risks are important issues in risk assessment. This article presents a novel occupational risk-assessment approach, which can help managers of shipbuilding make proper precautions strategies for accidents, to evaluate shipyard Critical Risk Factors and risky shipyard processes/work units. Thus, DEMATEL (Decision Making Trial and Evaluation Laboratory) and Grey system theory approaches are integrated to develop a systematic risk-assessment framework for the shipbuilding industry. This approach was applied to a real case study in a Turkish shipyard. The performance evaluation results have indicated that the combined approach can provide satisfactory risk assessment for occupational risk causes and relevant improvement strategies to prevent accidents. Sensitivity analysis was also conducted on the results to ensure the reliability of solutions. Even though a novel decision support and evaluation approach on risk implementation is introduced for shipbuilding, limitations and concerns are areas for further research opportunities. Further, a sensitivity analysis of results, managerial implications, conclusions, limitations and future research opportunities are provided.

A Hybrid Multicriteria Decision Making Methodology Based on Type-2 Fuzzy Sets For Selection Among Energy Storage Alternatives

AbstractEnergy storage alternatives that help storing excess energy and then using it when the system needs it has become more important in recent years. Determination of the most suitable energy storage alternative can be analyzed by using multi criteria decision making (MCDM) techniques. There are many criteria that affect the best energy storage alternative and the aims are contrasting so, MCDM methodology is a good approach to solve these problems. In this paper, a hybrid MCDM methodology that consists of analytic hierarchy process (AHP) and TOPSIS based on type-2 fuzzy sets is proposed. To obtain more flexible evaluation and more precise results the proposed methodology combines type-2 fuzzy AHP that used to determine the weights of criteria and type-2 fuzzy TOPSIS methodology that analyzes the alternatives with respect to criteria and weights. The proposed methodology has been used to determine the most suitable energy storage alternatives. For this aim, 6 electrical energy storage alternatives are ...

Just-In Time Production System Using Fuzzy Logic Approach and a Simulation Application

While firms are operating in a global competitive environment, they are subjected to changes because of the increased competitiveness and developed technologies. Therefore, this transformation process forces to produce with just-in-time production and low cost products or services and leads to customer satisfaction. Until today, competitive conditions, efficiency, productivity and quality of production, forced the firms to put more emphasis on production systems. Therefore, the firms are more interested in scientific analysis, planning and controlling of their production systems. As a result, one of the newest approaches is Just in Time (JIT) production system which emerged after WWII in Japan and aims to decrease the inventory cost and maximize the quality. The philosophy of this approach is to produce the necessary amount of production, when and where needed at the required quality. But JIT production system is weak in unclear species. For this purpose, the general and necessary solution is using fuzzy logic. In this paper we discussed about the simulation of an assembly line with 3 steps; firstly using Kanban production method, secondly non-using Kanban production method, and lastly using Kanban production method with fuzzy times. And also the comparisons of these steps will also be studied in this paper.