Mixed truck delivery systems with both hub-and-spoke and direct shipment

Department of Shipping and Transport Logistics2003-2004 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

DESAIN LOKASI GUDANG ANTARA DAN OPTIMISASI RUTE KENDARAAN PENGANGKUT AIR MINERAL DI PT. MUAWANAH AL-MA’SOEM KOTA BANDUNG (STUDI KASUS : PT. MUAWANAH AL-MA’SOEM KOTA BANDUNG)

PT. Muawanah Al-Ma’soem merupakan salah satu perusahaan air minum dalam kemasan yang berpusat di Bandung tepatnya di Kabupaten Bandung yaitu Cileunyi. PT. Muawanah Al-Ma’soem memliki 4 gudang antara yaitu Cikalang (Pusat), Bandung, Rajamandala, dan Limbangan. Salah satu produk yang dimiliki oleh PT. Muawanah Al-Ma’soem yaitu produk air minum dalam kemasan jenis cup 240 ml yang dikemas dalam kemasan karton yang berisi 48 cup per karton. Permasalahan yang terjadi di PT. Muawanah Al-Ma’soem terdapat pada pendistribusian yang dilakukan oleh gudang antara Bandung terhadap ke 64 retail tujuan yang tersebar. Pada saat ini pola kegiatan pendistribusian gudang antara Bandung masih acak yang menyebabkan jarak dan lokasi retail yang dituju tidak efektif, belum terdapat jadwal pengiriman produk air minum dalam kemasan yang tetap sehingga pendistribusian dilakukan secara berulang ke setiap retail yang tersebar serta pemanfaatan kapasitas alat angkut yang belum optimal yang menyebabkan kendaraan belum mampu mendistribusikan produk dalam satu kali keberangkatan. Beberapa permasalahan tersebut menyebabkan biaya distribusi yang dikeluarkan oleh PT. Muawanah Al-Ma’soem menjadi tidak optimal. Oleh karena itu, penelitian ini dilakukan untuk memnetukan rute distribusi yang minimum agar biaya distribusi yang dikeluarkan oleh PT. Muawanah Al-Ma’soem menjadi lebih optimal dibandingkan dengan sebelumnya. Penyelesaian masalah dilakukan dengan empat langkah yaitu pertama, dengan melakukan pengelompokkan (clustering) wilayah pendistribusian dengan metode Fuzzy C Means agar kapasitas angkut kendaraan dapat dimaksimalkan untuk melayani setiap retail tujuan dalam satu kali keberangkatan. Kedua, penentuan fasilitas gudang antara menggunakan metode Hub Location Problem agar memperoleh gudang antara di salah satu retail yang berada pada suatu cluster. Ketiga, penentuan rute distribusi menggunakan metode Nearest Neighbor agar diperoleh rute distribusi dengan jarak terpendek ke setiap retail tujuan. Keempat, optimisasi rute distribusi dengan metode Simulated Annealling agar mendapatkan rute distribusi yang lebih optimal dari sebelumnya. Hasil dari penelitian yang dilakukan diperoleh 8 cluster wilayah pendistribusian, satu retail yang dijadikan gudang antara di setiap cluster, dan rute pendistribusian air minum dalam kemasan yang optimal. Dengan hasil pengehematan biaya distribusi yang diperoleh sekitar Rp 1.718.985 dengan efisiensi sebesar 28,69%. Kata Kunci: Vehicle Routing Problem, Capacitated Vehicle Routing Problem, Fuzzy C Means, Hub Locataion Problem, Nearest Neighbor, Simulated Annealling

Domestic flight network hub location problem under traffic disruption with sustainability provision

There are many models in the current literature used extensively for the last 20 years on hub location problems and collect-distributive network structures. A centrally hub located facility serves as the main distribution base and flows from other facilities are collected in this hub then distributed. This centralization approach and expansion of the operational network brings the advantage of economies of scale in these days. According to the airline companies, the flight network in form of a distributor increases the profit of airline companies and provides significant savings in costs. In this study, a new hub location problem as homogeneous multi allocation p-hub median problem is proposed and solved considering the effects of airplane types and characteristics on hub locations were investigated. The results showed that the constraints and parameters used in the developed model have a significant effect on hub site selection and assignment to the different flight routes of low-cost airline companies

Exact solution of hub network design problems with profits

This paper studies hub network design problems with profits. They consider a profit-oriented objective that measure the tradeoff between the revenue due to served commodities and the overall network design and transportation costs. An exact algorithmic framework is proposed for two variants of this class of problems, where a sophisticated Lagrangian function that exploits the structure of the problems is used to efficiently obtain bounds at the nodes of an enumeration tree. In addition, reduction tests and partial enumerations are used to considerably reduce the size of the problems and thus help decrease the computational effort. Numerical results on a set of benchmark instances with up to 100 nodes confirm the efficiency of the proposed algorithmic framework. The proposed methodology can be used as a tool to solve more complex variants of this class of problems as well as other discrete location and network design problems involving servicing decisions.Peer ReviewedPostprint (author's final draft

GRASP Metaheuristic for Multiple Allocation p-Hub Location Problem

Hub Location Problems (HLPs), belonging to the field of location theory, have been area of much research over the past two decades. This is due, in large measure, to the applications of hub and spoke networks in practice. Among the most classical versions of HLPs are p-hub location problems (p-HLPs), p-hub location problems are one of the most well studied variants of hub location literature. The primary goal of these models is to allocate p hub facilities in a hub and spoke network so as to concentrate flows (demands) to benefit from economies of scale in cost of transportation. The application of p-hub networks extends beyond the field of telecommunication and includes air freight systems, postal delivery systems and airline industries and several transportation related systems. p-HLPs constitute a challenging class of HLPs and are known to be NP-hard. Several solution approaches have been developed from exact solutions using integer programming techniques to the development of metaheuristics. Even though metaheuristic algorithms cannot guarantee optimality, given complexity of large scale HLPs, they are being used for solving these problems. In this thesis, we focus on the multiple allocation uncapacitated p-hub location problem. Four solution algorithms will be proposed to this problem for solving the Australian Postal (AP) data instances. We start with a very simple algorithm and continue with more complicated one in order to present an efficient high quality feasible solution and to assess the impact of the quality of initial feasible solution on local improvement phase. Computational results from the different algorithms were compared to exact solutions to track the efficiency of the proposed algorithms

Environmental and health benefits of airport congestion pricing - The case of Los Angeles International Airport

Airports are a source of greenhouse gases (GHG) and air pollutants such as fine particulate matter with an aerodynamic diameter under 2.5 μm (PM2.5), which adversely affect the climate and human health. This pollution is worsening with increasing aircraft congestion. Even though aviation is the second largest source of GHG emissions in the transportation sector, it was excluded from the recent COP21 Paris Agreement. Little is known about the climate change and adverse health impacts from increasing airports congestion. The purpose of this study is to start filling this gap. In this dissertation, I estimate congestion, health, and climate benefits from airport congestion pricing for Los Angeles International Airport (LAX), the fourth busiest airport in the world by passenger numbers in 2018. I first derive the optimal congestion fee for airports like LAX that primarily serve local and regional markets. To quantify the impacts of airport congestion pricing, I analyze one year of airport operations (2014), which corresponds to 593,547 flights (both inbound and outbound). My simulation results suggest that hourly congestion pricing would on average reduce waiting time by 2.9 minutes per flight and annual PM2.5 emissions by 11.4 percent, thus decreasing the environmental impacts from aircraft landing and takeoff operations (LTO), which extend as far as 19 km downwind from the airport.An analysis of the health gains from implementing a congestion fee that accounts for air pollution cost shows that it would annually reduce premature mortality from PM2.5 exposure by 4.6 cases, avoided hospital admissions for cardiovascular diseases by 167 cases, and avoid 8,539 lost work days. The corresponding monetary value of these health gains are $45.8 million,$21.9 million, and $1.4 million respectively (all in 2014 dollars).For my climate change analysis, I consider both the country-level social cost of carbon (CSCC;$36 per tonne) and the global social cost of carbon (GSCC; $417 per tonne). While pricing GHG emissions with the CSCC only has a minor impact, using the GSCC helps further reduce aircraft congestion and its associated health impacts. Indeed, an aircraft congestion fee with GHG based on the GSCC would reduce premature mortality by 6 cases each year, avoided hospital admissions by 221 cases, and avoid 11,528 lost work days (95$60.7 million, $27.7 million, and$1.9 million respectively.The methodology presented in this study is widely applicable. It provides engineers, planners, and policymakers a tool for reducing airport congestion and for quantifying the resulting health and climate benefits

Hub location problem for air-ground transportation sistems with time restrictions

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2006.Thesis (Master's) -- Bilkent University, 2006.Includes bibliographical references leaves 68-73.In this thesis, we study the problem of designing a service network for cargo delivery sector. We analyzed the structure of cargo delivery firms in Turkey and identified the features of the network. Generally, in the literature only one type of vehicle is considered when dispatching cargo. However, our analysis showed that in some cases both planes and trucks are used for a better service quality. Therefore, we seek a design in which all cargo between origin and destinations is delivered with minimum cost using trucks or planes within a given time bound. We call the problem “Time Constrained Hierarchical Hub Location Problem (TCHH)” and propose a model for it. The model includes some non-linear constraints. After linearizations, the TCHH is solved with data taken from cargo delivery firms. The computational results are reported and comparison with the current structure of a cargo delivery firm is given.Elmastaş, SedaM.S