Bulanık proje çizelgeleme problemlerinin paralel kanguru algoritmasıyla çözümü

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Günümüzde şirketler artık sadece kendi bölgelerinde değil, küreselleşmenin getirdiği küresel pazarda rekabet etmek durumundadırlar. Bu rekabetin bir neticesi olarak gün geçtikçe ürünlerin ömürleri azalırken ürün çeşitliliği artmakta, bu da belirsizliğin artmasına ve planlamanın güçleşmesine yol açmaktadır. Böyle bir ortamda ayakta kalabilmek için şirketlerin doğru kararlar alarak doğru planlar yapması gerekmekte ve bu durum da proje çizelgelemenin önemini artırmaktadır. Bu problemin çözümünde kesin çözüm veren yöntemlerin kullanılması hem gerçekçilik açısından hem de bunların hesaplanması için gerekli süre açısından uygun olmamaktadır. Belirsizliğin çözümünde en doğal yöntem bulanık küme teorisidir. Bu yöntemin proje çizelgelemede kullanılmasıyla daha etkili ve verimli çizelgeler oluşturmak mümkün olmaktadır. Bu tez çalışmasında, faaliyet sürelerinin ve bu faaliyetlerin kaynak ihtiyacının bulanık olduğu, yeni bir ürün geliştirme projesi problemi üzerinde durulmuştur. Bu problemde belirsiz ve esnek olan geçici bilginin modellenmesinde bulanık küme teorisi kullanılmış ve problemin çözümünde, en düşük çizelge riskinin belirlenmesi ve her bir faaliyetin bütün kısıtlarının minimum tatmin değerlerini maksimize edecek bir başlama zamanının tespit edilmesi için paralel kanguru algoritması kullanılmıştır. Önerilen yöntem, proje yöneticilerinin belirsiz bir çizelgeleme ortamında, geç kalma ihtimali en düşük olan bir çizelgeyi seçmelerine yardımcı olabilmektedir.Today, as a result of ongoing globalization, companies do not have to only compete on the local market but worldwide. Globalization also caused an increase in product variety while shortening product life. Consequent confusion and uncertainty made predicting the future and planning accordingly much more difficult. To survive in such environment, companies should make the right decisions, and this is increasing the importance of project scheduling. Because classic planning and scheduling methods fail to keep up in such an environment, to make right decisions and to draw accurate plans for future requires an unconventional approach. Using exact methods to solve these problems is not feasible, due to required long computational time and realism of the project. An alternative way to solve this uncertainty is the fuzzy set theory, which is a natural way to solve uncertainty. By using this method, it is possible to make more effective and efficient schedules for a project. In this thesis, the problem of a new product development project with fuzzy activity durations and fuzzy resource requirements studied. Fuzzy set theory is used to model the uncertain and flexible temporal information, and parallelized kangaroo algorithm is used to determine minimum schedule risk, and find a starting time for each activity, that maximizes the minimum satisfaction value of all constraints of all activities. The proposed method may help the project managers to choose a schedule in an uncertain scheduling environment with the lowest probability of being late

Solving Integrated Process Planning, Dynamic Scheduling, and Due Date Assignment Using Metaheuristic Algorithms

Because the alternative process plans have significant contributions to the production efficiency of a manufacturing system, researchers have studied the integration of manufacturing functions, which can be divided into two groups, namely, integrated process planning and scheduling (IPPS) and scheduling with due date assignment (SWDDA). Although IPPS and SWDDA are well-known and solved problems in the literature, there are limited works on integration of process planning, scheduling, and due date assignment (IPPSDDA). In this study, due date assignment function was added to IPPS in a dynamic manufacturing environment. And the studied problem was introduced as dynamic integrated process planning, scheduling, and due date assignment (DIPPSDDA). The objective function of DIPPSDDA is to minimize earliness and tardiness (E/T) and determine due dates for each job. Furthermore, four different pure metaheuristic algorithms which are genetic algorithm (GA), tabu algorithm (TA), simulated annealing (SA), and their hybrid (combination) algorithms GA/SA and GA/TA have been developed to facilitate and optimize DIPPSDDA on the 8 different sized shop floors. The performance comparisons of the algorithms for each shop floor have been given to show the efficiency and effectiveness of the algorithms used. In conclusion, computational results show that the proposed combination algorithms are competitive, give better results than pure metaheuristics, and can effectively generate good solutions for DIPPSDDA problems

Concurrent solution of WATC scheduling with WPPW due date assignment for environmentally weighted customers, jobs and services using SA and its hybrid

After industrial revolution environmental problems increased drastically. Air, water and soil pollution became a serious threat for the mankind. In order to overcome this threat everyone should take responsibility and try to preserve environment as much as possible. Environmentally conscious actions, people, law and foundations should be supported. When it came to determining due dates and scheduling, one of the important criteria should be the supporting the environment. In this study environmentally conscious customers, jobs, and services are rewarded, on the other hand unconscious customers, jobs, and services are penalized, while determining due dates and schedules. Simulated annealing and its hybrid with random search are applied to get environmentally better due dates and schedules

Modelling Porosity Permeability of Ceramic Tiles using Fuzzy Taguchi Method

Taguchi experiment design in quality development studies, is an approach to engineering that supports research and development, product design and product development activities by enabling fewer trials of experiments to determine the best combinations of inputs that affect the outcome. In this study, the factors affecting the porosity were studied in a firm that produces ceramic tile. There were 6 factors considered to be important in total and 2 levels in each factor. L8 orthogonal array were used during the experiment design, which proposes 8 experiment types with different factor levels. The results of the experiments were analyzed so that important factors were determined. Significance of factors were tested by ANOVA and 4 of them were found to be significant. These factors were fuzzified by assessing the factors using linguistic expressions and then triangular fuzzy numbers. A model with 4 inputs and 1 output was built and 34 rules were generated for this model. The developed model was shown to be a useful approach in modeling the porosity permeability of ceramic tiles

Dynamic bottleneck elimination in mattress manufacturing line using theory of constraints

There is a tough competition in the furniture sector like other sectors. Along with the varying product range, production system should also be renewed on a regular basis and the production costs should be kept under control. In this study, spring mattress manufacturing line of a furniture manufacturing company is analyzed. The company wants to increase its production output with new investments. The objective is to find the bottlenecks in production line in order to balance the semi-finished material flow. These bottlenecks are investigated and several different scenarios are tested to improve the current manufacturing system. The problem with a main theme based on the elimination of the bottleneck is solved using Goldratt and Cox's theory of constraints with a simulation based heuristic method. Near optimal alternatives are determined by system models built in Arena 13.5 simulation software. Results show that approximately 46 % capacity enhancements with 2 buffer stocks have increased average production by 88.8 %

A Novel Hypogenetic Chaotic Jerk System: Modeling, Circuit Implementation, and Its Application

When revising the polarity and amplitude information in the feedback, a unique hypogenetic jerk system was obtained which has two controllers to switch the equilibria between stable and unstable. After providing some basic dynamical analysis, an electronic circuit was implemented, and the phase trajectory in the oscilloscope agrees with the numerical simulation. Further exploration shows that this unique chaotic system has superior performance as a random number generator or in voice encryption application