Browsing by Subject "Vehicle routing"
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Item Open Access Arçelik yurt içi tedarik zinciri için araç sevkiyat ve rotalama sistemi(Makina Mühendisleri Odası, 2009) Tansel, Barbaros; Daşyürek, Fatma; Eren, Semih; Kaya, Özge; Sezgin, Gökhan; Şahinoğlu, EbruBu çalışmada tedarikçilerden gelen malzemelerin Arçelik Bulaşık Makinesi İşletmesi’ne taşınması için kullanılacak rotaların ve taşıyıcıların hareket çizelgelerinin optimal veya optimale yakın bulunması amacıyla bir karar destek sistemi oluşturulmuştur. Sistem matematiksel model, benzetim modeli ve arayüz olmak üzere üç ana öğeden oluşmaktadır. Tedarikçi kümesinde veya tedarikçi taleplerinde olabilecek olası küçük değişimlere karşı önerilen çözümler benzetim modeli yoluyla hızlı bir şekilde değerlendirilebilmekte, büyük değişimler olduğunda ise matematik model yeniden çözülerek yeni optimal çözüm elde edilmektedir. Arayüz programı, her iki modelin teknik bilgilere sahip olunmasa bile daha kolay kullanılmasını sağlamaktadır.Item Open Access A branch and cut algorithm for the inventory routing problem(Bilkent University, 2019-07) Mahmutoğulları, ÖzlemThe inventory routing problem arises in vendor managed systems where products are distributed from a supplier to a set of retailers by a homogeneous eet of capacitated vehicles. The routes of the vehicles and the quantities of products sent to each retailer in each time period are determined in such a way that no stockouts occur and total costs arising from inventory holding and transportation are minimized. Different inventory replenishment policies can be used while managing the inventories at retailers. We consider the problem with the maximum level inventory replenishment policy. We present a mixed integer linear programming model and derive valid inequalities using several structured relaxations. We relate our valid inequalities to those in the previous studies. We also propose new valid inequalities, implement a branch and cut algorithm and present computational results on benchmark instances from the literature as well as new randomly generated instances.Item Open Access A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations(Elsevier Ltd, 2017) Ozbaygin G.; Ekin Karasan O.; Savelsbergh M.; Yaman, H.We study the vehicle routing problem with roaming delivery locations in which the goal is to find a least-cost set of delivery routes for a fleet of capacitated vehicles and in which a customer order has to be delivered to the trunk of the customer's car during the time that the car is parked at one of the locations in the (known) customer's travel itinerary. We formulate the problem as a set-covering problem and develop a branch-and-price algorithm for its solution. The algorithm can also be used for solving a more general variant in which a hybrid delivery strategy is considered that allows a delivery to either a customer's home or to the trunk of the customer's car. We evaluate the effectiveness of the many algorithmic features incorporated in the algorithm in an extensive computational study and analyze the benefits of these innovative delivery strategies. The computational results show that employing the hybrid delivery strategy results in average cost savings of nearly 20% for the instances in our test set. © 2017 Elsevier LtdItem Open Access Exact solution approaches for non-Hamiltonian vehicle routing problems(Bilkent University, 2017-07) Özbaygın, Amine GizemIn this thesis, we study di erent non-Hamiltonian vehicle routing problem variants and concentrate on developing e cient optimization algorithms to solve them. First, we consider the split delivery vehicle routing problem (SDVRP).We provide a vehicle-indexed ow formulation for the problem, and then, a relaxation obtained by aggregating the vehicle-indexed variables over all vehicles. This relaxation may have optimal solutions where several vehicles exchange loads at some customers. We cut-o such solutions either by extending the formulation locally with vehicle-indexed variables or by node splitting. We compare these approaches using instances from the literature and new randomly generated instances. Additionally, we introduce two new extensions of the SDVRP by restricting the number of splits and by relaxing the depot return requirement, and modify our algorithms to handle these extensions. Second, we focus on a problem unifying the notion of coverage and routing. In some real-life applications, it may not be viable to visit every single customer separately due to resource limitations or e ciency concerns. In such cases, utilizing the notion of coverage; i.e., satisfying the demand of multiple customers by visiting a single customer location, may be advantageous. With this motivation, we study the time constrained maximal covering salesman problem (TCMCSP) in which the aim is to nd a tour visiting a subset of customers so that the amount of demand covered within a limited time is maximized. We provide ow and cut formulations and derive valid inequalities. Since the connectivity constraints and the proposed valid inequalities are exponential in the size of the problem, we devise di erent branch-and-cut schemes. Computational experiments performed on a set of problem instances demonstrate the e ectiveness of the proposed valid inequalities in terms of strengthening the linear relaxation bounds as well as speeding up the solution procedure. Moreover, the results indicate the superiority of using a branch-and-cut methodology over a ow-based formulation. Finally, we discuss the relation between the problem parameters and the structure of optimal solutions based on the results of our experiments. Third, we study the vehicle routing problem with roaming delivery locations (VRPRDL) in which a customer order has to be delivered to the trunk of the customer's car during the time that the car is parked at one of the locations in the (known) customer's travel itinerary. We formulate the problem as a set covering problem and develop a branch-and-price algorithm for its solution. The algorithm can also be used for solving a more general variant in which a hybrid delivery strategy is considered that allows a delivery to either a customer's home or to the trunk of the customer's car. We evaluate the e ectiveness of the many algorithmic features incorporated in the algorithm in an extensive computational study and analyze the bene ts of these innovative delivery strategies. The computational results show that employing the hybrid delivery strategy results in average cost savings of nearly 20% for the instances in our test set.Finally, we consider the dynamic version of the VRPRDL in which customer itineraries may change during the execution of the planned delivery schedule, which can become infeasible or suboptimal as a result. We refer to this problem as the dynamic VRPRDL (D-VRPRDL) and propose an iterative solution framework in which the previously planned vehicle routes are re-optimized whenever an itinerary update is revealed. We use the branch-and-price algorithm developed for the static VRPRDL both for solving the planning problem (to obtain an initial delivery schedule) and for solving the re-optimization problems. Since many re-optimization problems may have to be solved during the execution stage, it is critical to produce solutions to these problems quickly. To this end, we devise heuristic procedures through which the columns generated during the previous branch-and-price executions can be utilized when solving a re-optimization problem. In this way, we may be able to save time that would otherwise be spent in generating columns which have already been (partially) generated when solving the previous problems, and nd optimal solutions or at least solutions of good quality reasonably quickly. We perform preliminary computational experiments and report the results.Item Open Access The green location-routing problem(Elsevier, 2019) Dükkancı, Okan; Kara, Bahar Y.; Bektaş, TolgaThis paper introduces the Green Location-Routing Problem (GLRP), a combination of the classical Location-Routing Problem (LRP) and the Pollution-Routing Problem (PRP). The GLRP consists of (i) locating depots on a subset of a discrete set of points, from where vehicles of limited capacity will be dispatched to serve a number of customers with service requirements, (ii) routing the vehicles by determining the order of customers served by each vehicle and (iii) setting the speed on each leg of the journey such that customers are served within their respective time windows. The objective of the GLRP is to minimize a cost function comprising the fixed cost of operating depots, as well as the costs of the fuel and CO2 emissions. The amount of fuel consumption and emissions is measured by a widely used comprehensive modal emission model. The paper presents a mixed integer programming formulation and a set of preprocessing rules and valid inequalities to strengthen the formulation. Two solution approaches; an integer programming based algorithm and an iterated local search algorithm are also presented. Computational analyses are carried out using adaptations of literature instances to the GLRP in order to analyze the effects of a number parameters on location and routing decisions in terms of cost, fuel consumption and emission. The performance of the heuristic algorithms are also evaluated.Item Open Access The green network design problem(Elsevier, 2019) Dükkancı, Okan; Bektaş, T.; Kara, Bahar Y.; Faulin, J.; Grassman, S. E.; Juan, A. A.; Hirsch, P.Logistics activities are at the heart of world trade, but they also have unintended consequences on the environment due to the use of land, energy, and other types of natural resources. The significant energy usage by the more traditional means of transportation results in emissions, one of the most prominent of all negative externalities, that in turn causes air pollution affecting human health. One way to reduce such externalities is the (re-)design of the overall network on which logistics activities take place, giving rise to green network design problems, where the minimization of emissions is an integral and explicit part of the objective. The aim of this chapter is to present an overview and a classification of green network design problems arising at different levels of decision making, from operational to strategic, and will present definitions, optimization models, and practical applications for some of the key problems in this category.Item Open Access Hub location and routing problem(Bilkent University, 2016-01) Bayraktar, SinanHubs are special facilities that consolidate and disseminate ows in many-to-many distribution systems. The hub location problem aims to nd locations of hubs and allocate non-hub nodes directly to the hubs. However, this problem is necessary to extend when nodes do not have su cient demand to justify direct connections between the non-hub nodes to the hubs since such direct connections increase the number of vehicles required and decrease the utilization of vehicles. Hence, it is necessary to construct local tours among the nodes allocated to the same hubs to generate economies of scale and to decrease vehicle costs. Nevertheless, forcing each non-hub node to be visited by a local tour is not the best way to design a many-to-many distribution system. Therefore, in this study two options for each non-hub node are given: (i) either it could be visited by a local tour or (ii) it could be directly connected to a hub without an economy of scale. We develop a mixed integer programming formulation and strengthen it with valid inequalities. We also develop three di erent Benders formulations as exact solution methods. In addition, we develop a hierarchical heuristic with two phases in order to solve large-sized problem instances. We test the performances of our solution methodologies on CAB and TR data sets.Item Open Access Solving school bus routing problems through integer programming(Palgrave Macmillan Ltd., 2007) Bektaş, T.; Elmastaş, S.In this paper, an exact solution approach is described for solving a real-life school bus routing problem (SBRP) for transporting the students of an elementary school throughout central Ankara, Turkey. The problem is modelled as a capacitated and distance constrained open vehicle routing problem and an associated integer linear program is presented. The integer program borrows some well-known inequalities from the vehicle routing problem, which are also shown to be valid for the SBRP under consideration. The optimal solution of the problem is computed using the proposed formulation, resulting in a saving of up to 28.6 in total travelling cost as compared to the current implementation. © 2007 Operational Research Society Ltd. All rights reserved.