Belirsizlik altında heterojen filo ve zaman pencereli rotalama problemi: Hızlı tüketim sektöründe bir uygulama
Heterogeneous vehicle routing with time windows under uncertainty: Implementation in fast moving goods industry
Yazar: ELÇİN ÖZEN KURU
Danışman: PROF. DR. FERHAN ÇEBİ
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / İşletme Mühendisliği Ana Bilim Dalı / İşletme Mühendisliği Bilim Dalı
Derece: Yüksek Lisans, 2018
Konu: Endüstri ve Endüstri Mühendisliği = Industrial and Industrial Engineering

Özet:
Günümüz artan rekabet koşullarında firmalar sürekli gelişerek değişen koşullara uyum sağlamaya ve pazardaki paylarını arttırmaya çalışmaktadırlar. Pazarda bir çok alternatifin bulunduğu günümüzde, firmalar rekabet güçlerini ellerinde bulundurabilmek için yüksek kalite ve çeşitlilikte olan ürünlerini düşük maliyet ve yüksek servis hızı ile müşterilene ulaştırmak zorundadırlar.Ancak müşteri memnuniyetini arttırmak için hızlı ve esnek yapılar kurulurken, karlılıkların da kontrol altında tutulabilmesi önemlidir.Bu sebeple firmalar sürekli olarak maliyetlerini düşürme hedefindedirler.Etkin bir tedarik zinciri yönetimi, maliyetleri dengelemek için etkili bir araçtır. Müşterilere gereken ürünleri istenilen miktar ve zamanda ulaştırırken bir yandan da tedarikçilerle etkin bir biçimde çalışarak ham maddeleri istenilen zamanda ve düşük maliyetlerle tedarik etmek gerekmektedir.Lojistik maliyetleri işletmelerin toplam maliyetlerinin %6-20'sine karşılık gelmektedir. Bu sebeple lojistik yönetiminin en önemli faaliyetlerinden biri olan dağıtım alanında yapılan iyileştirmeler firmaların karlılıklarına önemli katkılar sağlamaktadır. 

Araç rotalama problemleri dağıtım yönetiminin merkezini oluşturmaktadır.Araç rotalama problemlerinde talebin yapısı, araçların çeşitliliği, taşınacak malzemelerin tipi, dağıtım/toplama noktalarının lokasyonları, kapasite ve zaman gibi girdilere göre araçların müşterilere/tedarikçilere atamasını gerçekleştirerek, süreçlerdeki verimliliklerin arttırılıp, lojistik maliyetlerinin düşürülmesini amaçlanmaktadır.

Yapılan bu çalışma, bir firmanın ihtiyaçlarından yola çıkılarak üretilmiştir. İşletmenin lojistik maliyetlerini düşürebilmek için ham madde tedarik ağı planlaması yapılmıştır.İncelenen işletmenin depolama, zaman gibi kısıtları ve maliyet düşürme amacı gözönüne alınarak problem bir araç rotalama problemine dönüştürülmüştür.Problem yapısının daha iyi anlaşılabilmesi için öncelikle araç rotalama problemlerinin türleri ve litaratürde kullanılmakta olan çözüm yöntemlerinden bahsedilmiştir.Tezin daha sonraki kısımlarında ise, problemin amaçlarında bazı belirsizlikler olması nedeni ile bulanık kümeler ve bulanık programlama üzerinde durulmuş, tez kapsamında geliştirilen çok amaçlı karma tam sayılı doğrusal programlama modelinin çözümünde bulanık küme ve bulanık modellemeden yararlanılmıştır.Bulanık çok amaçlı modelin geleneksel tek amaçlı doğrusal programlama modeline dönüştürülmesinde arttırılmış max-min modeli kullanılmıştır. Modelin çözümünde GAMS 24.1 solver'ından yararlanılmış ve firma yetkililerinin belirlediği başarılma derecelerine göre en iyi çözümler elde edilmeye çalışılmıştır.Son olarak elde edilen sonuçlara göre firmanın kazanımları tartışılmış ve gelecek çalışmalar için önerilerde bulunulmuştur.

Abstract:
In today's increasing competitive conditions, firms try to adapt to changing conditions
and increase their market share with constantly evolving. Nowadays, there are many
alternatives in the market because of that companies must deliver high quality and
diversity products to customers with low cost and high service speed in order to
maintain their competitive power. However, while increasing customer satisfaction
with having a quick and flexible structure, also profitability need to be kept under
control. Therefore, firms need to constantly aim to reduce their costs. An efficient
supply chain management is an effective tool for balancing costs. While delivering the
required products to customers in the desired quantity and time, it is necessary to work
with suppliers efficiently to supply raw materials at the desired time with low costs.
Supply chain does not contains only manufacturers, suppliers and distributors. It is also
contain warehouse management, carriers and customers. In recent years, firms realized
that they can not gain competitive advantage in the market with only established their
marketing strategies.They should design effective supply chain network to sustain their
market share. Logistics costs correspond to between six and twenty percent of the
total cost of companies. Distribution is one of the most important activity of logistic
management. For this reason, improvements in distribution area provide significant
contributions to the profitability of companies.

Vehicle routing problems constitute the center of distribution management. According
to inputs such as the structure of demand, diversity of vehicles, the type of materials,
locations of distribution and collection points, capacity and time, the assignment of
vehicles to customers or suppliers is done to increase the efficiency of processes and
reduce logistics costs. In general, the main objectives of vehicle routing problems are
as follows: Minimizing the total route cost, minimizing the costs of vehicles (fixed
costs or variable costs), minimizing the total route time, minimizing the number of
vehicles, minimizing routes times, if there are customers who cannot meet the their
demand on time or in full, minimizing the total penalty cost for these customers. In
addition, some studies in the literature have been used often workload balancing as a
second goal of vehicle routing problems. The first study in vehicle routing problems
was done by Dantzing and Ramser in 1959. This study aims to provide an optimal
routing plan with using homogeneous vehicle fleets. Five years after this study, Clarke
and Wright extended this study as optimisation problem and created today's vehicle
routing problem. However, with the increase of the complex structures of today's
firms, presented models in 1960s are insufficient to respond to company needs. For
this reason, for solving the real life problems heuristic and meta- heuristics approaches
have been developed.

In many methods developed for vehicle routing problems, the problem parameters
are are considered to be known, precise, and unchanging data. But in real life,especially in the transportation industry there are many uncertainties, and these
uncertainties have made the problems very complicated. Using the exact solution
methods for such problems and trying to achieve the best solution make the problems
more complicated by making the solution impossible. Therefore, considering today's
competitive conditions, instead of wasting unnecessary money and time for the best
solution, searching for the best solution for the best will bring more viable solutions.
Heuristic and Meteheuristic methods aim to find the closest solution to the best to
minimize the time spent solving the problem.

On the other hand, in real life problems there are uncertainties due to lack of
information. For the solutions of this kind of vague, probability theory and statistics
have been used for many years. Both methods use a logic that relies on the truth in
suggestions, meaning that a proposition is either true or false. However, expressions
may not always be clear. They can be partially true or partially wrong and this cause
to fuzzy environments. If information is not mathematically precise and clear, solution
of the classical methods does not provide results. For this reason Zadeh was developed
fuzzy logic and fuzzy set theory. According to Zadeh, if we have more information
about the system, complexity in the problems is reduced. On the other hand, as the
complexity increases, definite and meaningful expressions can not be established and
uncertainty occurs. Zadeh celled this situation as fuzzy.

The developed model under this study is provided by the needs of an industrial
organization which is operating in the fast moving consumer goods industry. Due
to there is no enough storage areas in the plant, the company has rented another
warehouse. But due to the high cost of renting a warehouse and material movements
between the main depot and the rental warehouse, significant increase in production
expenses was realized. For this reason, efforts have been initiated to reduce
transportation and storage costs by planning and logistics departments. In this study, it
was determined that, the 53% of raw materials which hold in the rental warehouse are
belong to only eight local suppliers. For this reason, to reduce shipping and storage
costs, vehicle routing plan was designed for raw material collection network. With
this new design, assigned trucks collect the goods and delivery the goods to directly
to plant. The trucks should leave from the plant and should return back to the factory
by collecting raw materials from suppliers. Purchased products should be delivered
directly to the main warehouse in the factory without being stocked in the rental
warehouse.

The first goal to be achieved with the solution of the problem is minimizing the total
route cost. In addition, completion material collection operations in the minimum time
is important for the company. The manufacturer is working with a carrier company for
raw material procurement. This company has different types of trucks. For this reason,
total processing times have been added to the model as a second goal and the problem
has been transformed to multi-objective mixed integer linear programming model
with heterogeneous fleet. Due to each supplier has defined time zones for material
loading, time windows were added the models.In addition that firm has two different
satisfaction degrees for goals of models, and this situation cause the uncertainty. To
eliminate uncertainties, multi-objective mixed-integer linear programming model is
solved by fuzzy modelling.
For the solution of the model, augmented max-min model was used to transform
fuzzy objective model to the single objective function model. Augmented model was
preferred due to give more balanced solutions. GAMS 24.1 solver was used for the
solution of the model.

According to the results obtained, products from eight suppliers can be taken with a
total of four vehicles. Total cost of routes was calculated as 3026 TL and all vehicles
return to factory until 14 o'clock so the factory can be used same trucks for internal
movements again. Because the products were directly placed in the production site
without being stored in the rental warehouse, thirty percent profit was achieved in total
cost due to the reduction in storage and internal transports.
In this master thesis, the data of a real problem was used and the solution was
calculated according to this data. But some assumptions were used for simplify
the problem. As an example, the changes in demand are not considered as part of
the thesis. In real life applications there will be cases where demand is uncertain.
Therefore, it is suggested that the model can be expanded for cases where the demand
is uncertain. In addition that, If the number of suppliers and vehicles in the model
increases, the solution of the model will take a long with exact solution methods. For
this reason heuristic and meta-heuristics approaches can be used in future studies.