In this paper we present a case study which involves the design of a supply chain network for industrial waste collection. The problem is to transport metal waste from 17 factories to containers and from containers to a disposal center (DC) at an organized region of automobile parts suppliers. We applied the classic mixed-integer programming (MIP) model for the two-stage supply chain to the solution of this problem. The visualization of the optimal solution provided us with several interesting insights that would not be easily discovered otherwise.

Martagan, T. G., Ertek, G., Birbil, S. I., Yasar, M., Cakır, A., Okur, N., Gullu, G., Hacıoglu, A. and Sevim, O. (2006). “Optimizing waste collection in an organized industrial region: A case study.” 4th International Logistics and Supply Chain Congress, İzmir, Turkey.

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Optimizing Waste Collection in an Organized Industrial Region: A Case Study

Dr. Gürdal Ertek recommends the following related books:

Spreadsheet Modeling and Applications: Essentials of Practical Management Science (with CD-ROM and InfoTrac) 1st Edition

Facility Layout and Location: An Analytical Approach (2nd Edition) 2nd Edition

 

Designing and Managing the Supply Chain 3e with Student CD 3rd Edition

 

 

 

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Association mining is one of the most used data mining techniques due to interpretable and actionable results. In this study we propose a framework to visualize the association mining results, specifically frequent item sets and association rules, as graphs. We demonstrate the applicability and usefulness of our approach through a Market Basket Analysis (MBA) case study where we visually explore the data mining results for a supermarket data set. In this case study we derive several interesting insights regarding the relationships among the items and suggest how they can be used as basis for decision making in retailing.

Ertek, G. and Demiriz, A. (2006). “A framework for visualizing association mining results.” Lecture Notes in Computer Science, vol: 4263, pp. 593-602.

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ertek_demiriz_iscis2006

Dr. Gürdal Ertek recommends the following related books:

Analyzing Social Media Networks with NodeXL

Data Mining Concepts and Techniques

Post-Mining of Association Rules

 

 

 

In this paper, we described an application of the Analytic Hierarchy Process (AHP) for the ranking and selection of forecasting software. AHP is a multi-criteria decision making (MCDM) approach, which is based on the pair-wise comparison of elements of a given set with respect to multiple criteria. Even though there are applications of the AHP to software selection problems, we have not encountered a study that involves forecasting software. We started our analysis by filtering among forecasting software that were found on the Internet by undergraduate students as a part of a course project. Then we processed a second filtering step, where we reduced the number of software to be examined even further. Finally we constructed the comparison matrices based upon the evaluations of three “semi-experts”, and obtained a ranking of forecasting software of the selected software using the Expert Choice software. We report our findings and our insights, together with the results of a sensitivity analysis.

Pekin, A., Ozkan, G., Eski, O., Karaarslan, U., Ertek, G. and Kilic, K. (2006). “Application of the analytic hierarchy process (AHP) for selection of forecasting software.” 5th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Application of the Analytic Hierarchy Process (AHP) for Selection of Forecasting Software

Dr. Gürdal Ertek recommends the following related books:

Models, Methods, Concepts & Applications of the Analytic Hierarchy Process (International Series in Operations Research & Management Science) Softcover reprint of the original 1st ed. 2001 Edition

The Hierarchon: A Dictionary of Hierarchies (Analytic Hierarchy Process, Vol 5)

 

 

 

Packing problems deal with loading of a set of items (objects) into a set of boxes (containers) in order to optimize a performance criterion under various constraints. With the advance of RFID technologies and investments in IT infrastructures companies now have access to the necessary data that can be utilized in cost reduction of packing processes. Therefore bin packing and container loading problems are becoming more popular in recent years. In this research we propose a beam search algorithm to solve a packing problem that we encountered in a real world project. The 3D-MBSBPP (Multiple Bin Sized Bin Packing Problem) that we present and solve has not been analyzed in literature before, to the best of our knowledge. We present the performance of our proposed beam search algorithm in terms of both cost and computational time in comparison to a greedy algorithm and a tree search enumeration algorithm.

Ertek, G. and Kilic, P. (2006). “Decision support for packing in warehouses.” Lecture Notes in Computer Science, vol: 4263, pp. 115-124.

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Decision Support For Packing In Warehouses

Dr. Gürdal Ertek recommends the following related books:

Introduction to Algorithms, 3rd Edition (MIT Press) 3rd Edition

World-Class Warehousing and Material Handling 1st Edition

How to Solve It: Modern Heuristics Enlarged 2nd Edition

 

 

 

 

 

 

 

 

 

We developed a spreadsheet optimization model to find the optimal material handling policy at a leading yarn and tire cord manufacturer’s facility. The focus of the study is to optimize the movement of looms of yarn and tire cord between two major manufacturing steps. The considered flow network within the manufacturing facility is a miniature two-stage supply chain, including the middle layer of depots. Movement of material takes place through forklift trucks and cranes, which impose electricity, labor, maintenance, and depreciation costs. After introducing the company, the facility, and the project goals, we present the underlying linear programming (LP) model and our spreadsheet implementation. The results of our model suggest an annual saving of approximately $22,000 for the facility.

Mataraci, B. and Ertek, G. (2006). “Spreadsheet optimization of flow for WIP goods at a yarn and tire cord manfacturer: A case study.” 5th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey.

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Spreadsheet Optimization of Flow for WIP Goods at a Yarn and Tire Cord Manufacturer: A Case Study

Dr. Gürdal Ertek recommends the following related books:

Spreadsheet Modeling and Applications: Essentials of Practical Management Science (with CD-ROM and InfoTrac) 1st Edition

 

Network Flows: Theory, Algorithms, and Applications 1st Edition

 

 

 

We developed an interactive simulation program to be used in industrial engineering education, based on an earlier simulation study of a steel cord manufacturing plant. In the class project, the students are asked to design strategies/algorithms for finding the optimal values of operational decision variables by using the program.

Saka, B., Ertek, G. and Turkseven, C. H. (2006). “Development of an interactive simulation of steel cord manufacturing for industrial engineering education.” 5th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey.

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Development Of An Interactive Simulation Of Steel Cord Manufacturing Forindustrial Engineering Education

Dr. Gürdal Ertek recommends the following related books:

Discrete-Event System Simulation (5th Edition)

Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management) 5th Edition

 

 

 

 

This paper presents an application of the well-known cutting stock problem to a construction firm. The goal of the 1Dimensional (1D) cutting stock problem is to cut the bars of desired lengths in required quantities from longer bars of given length. The company for which we carried out this study encounters 1D cutting stock problem in cutting steel bars (reinforcement bars) for its construction projects. We have developed several solution approaches to solving the company’s problem: Building and solving an integer programming (IP) model in a modeling environment, developing our own software that uses a mixed integer programming (MIP) software library, and testing some of the commercial software packages available on the internet. In this paper, we summarize our experiences with all the three approaches. We also present a benchmark of existing commercial software packages, and some critical insights. Finally, we suggest a visual approach for increasing performance in solving the cutting stock problem and demonstrate the applicability of this approach using the company’s data on two construction projects.

Alp, S., Ertek, G. and Birbil, S. I. (2006). “Application of the cutting stock problem to a construction company: A case study.” 5th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Application of the Cutting Stock Problem to a Construction Company: A Case Study

Dr. Gürdal Ertek recommends the following related books:

Operations Research: An Introduction (9th Edition) 9th Edition

Optimization in Operations Research 1st Edition