Süleyman Mete

Analysis of the type II robotic mixed-model assembly line balancing problem

ABSTRACT In recent years, there has been an increasing trend towards using robots in production systems. Robots are used in different areas such as packaging, transportation, loading/unloading and especially assembly lines. One important step in taking advantage of robots on the assembly line is considering them while balancing the line. On the other hand, market conditions have increased the importance of mixed-model assembly lines. Therefore, in this article, the robotic mixed-model assembly line balancing problem is studied. The aim of this study is to develop a new efficient heuristic algorithm based on beam search in order to minimize the sum of cycle times over all models. In addition, mathematical models of the problem are presented for comparison. The proposed heuristic is tested on benchmark problems and compared with the optimal solutions. The results show that the algorithm is very competitive and is a promising tool for further research.

A beam search approach for solving type II robotic parallel assembly line balancing problem

Abstract In a robotic assembly line, a series of stations are arranged along a conveyor belt and a robot performs on tasks at each station. Parallel assembly lines can provide improving line balance, productivity and so on. Combining robotic and parallel assembly lines ensure increasing flexibility of system, capacity and decreasing breakdown sensitivity. Although aforementioned benefits, balancing of robotic parallel assembly lines is lacking – to the best knowledge of the authors- in the literature. Therefore, a mathematical model is proposed to define/solve the problem and also iterative beam search (IBS), best search method based on IBS (BIBS) and cutting BIBS (CBIBS) algorithms are presented to solve the large-size problem due to the complexity of the problem. The algorithm also tested on the generated benchmark problems for robotic parallel assembly line balancing problem. The superior performances of the proposed algorithms are verified by using a statistical test. The results show that the algorithms are very competitive and promising tool for further researches in the literature.

Forward Supply Chain Network Design Problem: Heuristic Approaches

Öz Determining positions and counting of actors, amount of product flow between and decreasing transportation costs are handled as a network design problem in supply chain management. Supply chain network design (SCND) problem belongs to the class of NP-hard problems. It has therefore appealed to a number of researchers’ close attention. However, existing literature lacks of common benchmark instances for forward SCND problems so as to make a fair comparison between developed and applied heuristic approaches. To this end, 450 new benchmark instances ranging from small to large size for forward SCND problems with two, three and four-echelon are generated and a mathematical model for each of the problems is formulated. Due to the complexity issues, we develop two heuristic solution approaches, genetic algorithm (GA) and hybrid heuristic algorithm (HHA), and we apply them to the large pool of benchmark instances. Comparative experiments show that both the GA and HHA can yield feasible solutions in much less computational time and, in particular, outperforms CPLEX regarding the solution quality as the number of echelon grows. Tedarik zinciri içindeki tesislerin yerlerinin belirlenmesi, aralarındaki ürün akışlarının maliyeti minimize edecek şekilde optimize edilmesi tedarik zinciri ağ tasarımı (TZAT) problemi olarak karşımıza çıkmaktadır. TZAT problemleri NP-zor sınıfına girmektedir. Dolayısıyla çoğu araştırmacı tarafından üzerinde çalışılan bir konudur. Ancak literatürde araştırmacıların adil karşılaştırmalar yapabileceği test problemler mevcut değildir. Bu sebeple, küçük boyuttan büyük boyuta kadar iki, üç ve dört aşamalı olmak üzere 450 adet TZAT test problemi geliştirilmiş, matematiksel olarak da modellenmiştir. Problemin çözüm karmaşıklığından dolayı biri genetik algoritma diğeri de melez sezgisel bir yaklaşım olmak üzere iki farklı çözüm yöntemi önerilmiştir. Önerilen yaklaşımlar geliştirilen test problemlere uygulanmış ve karşılaştırmalar yapılmıştır. Elde edilen sonuçlara göre önerilen sezgisel yaklaşımlar küçük boyutlu problemler için CPLEX ile elde edilen optimal sonuçları yakalamış, büyük boyutlu problemler için ise çok daha kısa sürede kabul edilebilir sonuçlar elde etmiştir.

An optimisation support for the design of hybrid production lines including assembly and disassembly tasks

The optimisation problems related to the assignment of tasks to workstations in assembly and disassembly lines have been largely discussed in the literature. They are known, respectively, as Assembly Line Balancing and Disassembly Line Balancing Problems. In this study, both types of task performed on the identical product are integrated in a common hybrid production system. Therefore, the logistic process is simplified and disassembly tasks can supply easier the assembly tasks with the required components. The considered production system has the layout of two parallel lines with common workstations. The product flow is conventional in the assembly line and reverse in the disassembly line. The paper provides a new mathematical model for designing such a hybrid system and an approximate approach based on ant colony optimisation for solving large-scale instances. The solution method is tested in a case study. The obtained results are compared with the solution provided by the design of two independent lines. The analysis of the results highlights the potential benefits of the hybrid production system.

Location and Coverage Analysis of Bike- Sharing Stations in University Campus

Abstract Background: Bike-sharing programmes have become popular in a large number of cities in order to facilitate bicycle use. Determining the location of bike sharing stations is vital to success of these programmes. Objectives: In this paper, a case study is applied to the Gaziantep University campus in order to find possible locations of the stations for users (students). The purpose is to minimize the total walking distance. Methods/Approach: Set and maximal covering mathematical models are considered to decide on coverage capability of determined 20 demand points and 20 potential bike stations. Then, the mathematical models of P-center and P-median are used to build possible stations and to allocate demand points to the opened stations. Finally, an undesirable facility location model is used to find the bike stations, which have the maximum distance from demand nodes, and to eliminate them. Results: In computational results, it is clearly seen that the proposed approaches set the potential bike station covering all demand points. They also provide different solutions for the campus planners. Conclusions: The methodology outlined in this study can provide university administrators with a useful insight into locations of stations, and in this way, it contributes significantly to future planning of bike-sharing systems.

An efficient heuristic algorithm for solving robotic assembly line balancing problem

In the assembly system, robots provide to increase flexibility of the system and automation. The balancing robotic assembly line (RALB) problem consists two main works, which are not only assigning task to station, but also allocation robots in stations. Because each robots can perform different performance on the same tasks due to their capabilities. In this study, iterative beam search algorithm is developed to minimize cycle time. The performance of the algorithm outperforms other algorithm in the literature.

A heuristic algorithm for assembly line balancing with stochastic sequence-dependent setup times

Having analyzed studies on the assembly line balancing problem considering setup times, a few papers are observed. However, researches show that setup time plays an important role in total production time. Besides, in these studies, the setup times are assumed to be deterministic. Considering setup times to be deterministic decreases proximity of problem to real life application. Because the operation and setup times may vary in real applications due to human factors, machine breakdowns, lack of equipment and environmental factors. Therefore, in this study, assembly line balancing problem is investigated considering the sequence-dependent stochastic setup times. A heuristic approach based on COMSOAL is presented for the problem and it is seen that algorithm is effective for the problem.

A heuristic approach for joint design of assembly and disassembly line balancing problem

Balancing assembly and disassembly on parallel line together will positively affect to remanufacture production systems. In this study, two lines, which is one for assembly and other for disassembly, are considered as parallel line configuration. Parallelization of lines helps decrease the need for workforce significantly. Therefore, we propose heuristic approach based on ant colony optimization (ACO) for solving the balancing parallel line with minimizing number of workstations.