CEMENT TRANSPORTATION LIMITED-FLEET MODELING AND ASSIGNING TO RATED DEMANDS

Summary. Transportation is an inseparable part of the supply chain, with a key role in product distribution. This role is highlighted when ratio of "the cost of transportation" to "the value of goods" such as cement is significant. Iran has recently become one of the main centers of cement production in the world. However, transportation is the most important challenge in cement distribution because of weak structure of the transportation fleet and its independent action. Independence of and lack of commitment on the part of transportation fleets to cement companies as well as lack of timely delivery due to shortage of transportation in some routes and seasons lead to customers` dissatisfaction and even market loss or lack of market development. One of the significant differences between the transportation system in Iran and that in developed countries is lack of complete productivity of the transportation fleet. It means that trucks are driver-based in Iran. This paper introduces a model considering some issues such as driver-based trucks, size of the transportation fleet based on the number of active trucks, and demand priorities in the cement company. Taking the relation between the number of active trucks and the cement company into account, this model assigns weekly demands to the transportation fleet. It also tries to minimize the delay to respond to demands and increases the efficiency of the transportation fleet. Finally, this current condition-based model is compared with two other models including "no constraints on different routes of trucks" as well as single-route model for trucks

Optimasi Pencapaian EBITDA dengan Penerapan Strategi Alokasi Market Share di PT. XYZ

Tahun 2016 menjadi tahun titik balik dalam kurun waktu 15 tahun terakhir di industri persemenan Indonesia. Penurunan permintaan akibat terbatasnya pertumbuhan ekonomi dan juga bertambahnya pasokan semen dengan adanya pemain-pemain baru yang mulai berporoduksi, membuat harga jual sangat tertekan akibat semakin tingginya persaingan. Meskipun PT. XYZ sebagai salah satu pemain dominan dalam bisnis ini dan masih mendominasi market share di Indonesia, persaingan ini juga mengakibatkan penurunan market share yang pada akhirnya menurunkan tingkat keuntungan perusahaan. Earning before interest, taxes, depreciation and amortization (EBITDA) sebagai tolok ukur tingkat keuntungan perusahaan dibanding perusahaan lain di industri sejenis juga menunjukkan bahwa PT. XYZ mengalami penurunan yang cukup signifikan dari sebelumnya pernah mencapai EBITDA margin dengan angka tertinggi sebesar 35% di tahun 2012, menjadi sebesar 19.4% untuk pencapaian di tahun 2017. Penurunan EBITDA bisa dipengaruhi oleh faktor eksternal maupun faktor internal. Dari eksternal disebabkan oleh penurunan harga jual sekaligus penurunan pencapaian market share. Sedangkan dari sisi internal lebih dipengaruhi oleh kenaikan biaya yang disumbang oleh naiknya harga raw material dan bahan bakar. Penelitian ini fokus terhadap permasalahan yang disebabkan faktor eksternal yaitu penurunan market share. Dalam penelitian ini, langkah yang dilakukan adalah dengan melakukan maksimalisasi EBITDA dengan menggunakan model linear programming. Sebagai variabel keputusannya adalah jumlah volume semen terjual oleh tiap unit produksi di area penjualan tertentu yang berarti tahu posisi market sharenya. Adapun batasan-batasannya adalah kapasitas produksi tiap unit produksi dan target minimum dan maksimum market share untuk masing-masing area penjualan. Juga dilakukan simulasi untuk kondisi pasar yang berbeda yaitu kondisi kelebihan pasokan dimana permintaan pasar dibawah kapasitas produksi, dan juga kondisi kekurangan pasokan dimana jumlah permintaan pasar melebihi kapasitas produksi yang mampu dicapai unit produksi. Dari pemodelan yang dihasilkan, tercatat pencapaian EBITDA hasil optimasi sebesar Rp 462.954.808.834,- atau mengalami kenaikan sebesar 10.54% dari riil yang dicapai bulan Desember 2017. Pemodelan saat diuji pada kondisi normal, shortage maupun over capacity masih menghasilkan kenaikan pencapaian EBITDA yang cukup signifikan. Penelitian ini diharapkan akan dapat memberikan tambahan konsep terkait optimasi, serta dapat memberikan masukan bagi manajemen PT XYZ selaku pengambil keputusan untuk mengetahui alokasi market share untuk mendapatkan pencapaian EBITDA optimum. ================================================================================================= 2016 became a turning point for the last 15 years of cement industry in Indonesia. Demands declining based on limitation of the economic growth and also increasing of the cement supply related the new entrance that already began to start their full production capacity, making selling price become harder because of its intense competition. Although PT. XYZ as one of the dominant player for this business and still dominate their market share entire Indonesia, this condition made decreasing its market share that of course certain declining profit. Earning before interest, taxes, depreciation and amortization (EBITDA), as a benchmark of the company profit compared to other companies in similar industries also show us that PT. XYZ got its decreasing significantly. Highest rate of achievement that reached by 2012 for 35% EBITDA margin, decrease significantly to 19.4% in 2017. Its condition affected by an external factor and internal factor. For the external factor, decreasing selling price as well as decreasing market share were the dominant factors. While internal factor is more dominated by higher cost for raw material and fuel. This research focuses on the problem that affected by an external factor that is decreasing of market share. This research has aim to maksimizing EBITDA using linear programming model. As the decision variable used is total volume that sold by each production unit in a certain sales area wich means know its market share position. And for constraints there are production capacity for each production unit and also range of the minimum and maximum target of market share for each sales area. Simulation of the over capacity and shortage market condition will also tested using this model to gain insight. This model can achieved higher EBITDA than real condition in Desember 2017, that is Rp 462.954.808.834,- or increase significantly 10.54% than normal condition. This model also tested with normal, shortage and over capacity condition and can be concluded that this model gave higher EBITDA with such condition. Basically by this research we expected to provide additional concept according to optimization. And also provide consideration to PT. XYZ management as the decision makers for knowing best market shares allocation to get an optimum EBITDA

Study of mixed integer programming models for the concrete delivery problem

Objectives and Methods of Study: The main objective of this research is the study of Mixed Integer Programming (MIP) formulations for the Concrete Delivery Problem (CDP). Contributions and Conclusions: The main contribution of this thesis is two new compact MIP models. These formulations, based on a graph representation, reduce the number of used variables and restrictions involved in the problem and allow us to solve to optimality more instances than the mathematical models that have been presented in the literature for this proble

Distribución de commodities en PYMEs de comercio al por menor: Un enfoque cuantitativo

La gestión logística comprende las funciones de aprovisionamiento, distribución y devolución de bienes y productos físicos entre el productor y el consumidor final. En la función de distribución se encuentran actividades como la ubicación de centros logísticos, el almacenamiento, picking, packing, labeling, ruteo de vehículos y transporte, entre otras. El ruteo de vehículos, conocido en la literatura como VRP (Vehicle Routing Problem, en inglés), es un tema ampliamente discutido desde 1959, inicialmente por Dantzig y Ramser [21]. En la actualidad el VRP tiene muchas variantes que se ajustan a diferentes problemas de la vida real. Dado al continuo y acelerado avance de la ciencia y la tecnología, los métodos de solución actuales para los problemas de ruteo de vehículos desarrollados en las últimas cinco décadas son altamente complejos, lo anterior debido a que se han diseñado para satisfacer las necesidades de las grandes empresas en continuo crecimiento. Dichos modelos de ruteo requieren de alta tecnología para generar soluciones eficientes, precisas y oportunas. Específicamente las Pequeñas y Medianas Empresas (PYMEs) presentan desventajas relacionadas con los recursos disponibles, entre ellos el no contar con suficiente dinero para invertir en equipos y vehículos, para adquirir recursos tecnológicos o para emplear personal calificado para administrar y mantener tanto las plataformas y sistemas de distribución y ruteo de vehículos. Por otra parte las actividades de distribución de las PYMEs cuentan con características especiales, entre ellas, el uso de vehículos de baja capacidad (menores a 600 Kg) y velocidad, así como tiempos de respuesta cortos para atender las necesidades de sus clientes. Dadas las condiciones particulares de la PYMEs, la toma de decisiones relacionadas con el ruteo de vehículos debería soportarse en herramientas cuantitativas adecuadas para el grado de complejidad y teniendo en cuenta las características de sus operaciones de ruteo. Empleando una heurística de inserción sencilla para el problema de ruteo de vehículos con fraccionamiento de carga y ventanas de tiempo (SDVRPTW), implementada en una plataforma tecnológica común (Microsoft® Excel™) teniendo en cuenta las restricciones de recursos de las PYMEs, se validó que el SDVRPTW es un enfoque adecuado para abordar las necesidades de ruteo de vehículos en PYMEs sobre las otras variantes del problema, se redujo en un 50% el número de vehículos empleados para el caso de estudio, así como se validó que no se requieren recursos adicionales a los que ya cuentan las PYMEs para modelar sus operaciones de distribución empleando métodos cuantitativos.Abstract. Logistic management includes provisioning, distribution and return of goods and phisical products from provider to final customer. On distribution function there are activities like distribution centers location, storage, picking, packing, labeling, vehicle routing and transportation, among others. Vehicle routing, known as VRP is a widely discussed topic since 1959, firstly handled by Dantzig and Ramser [21]. Nowadays VRP has so many variants, which fits different real life problems. Given the continued and accelerated progress of science and technology, current solution methods for vehicle routing problems developed in the last two decades are highly complex, that is because they have been designed to meet the needs of the big companies in continuous growing, which have a large number of customers. Those routing models need high technology to generate efficient, accurate and timely solutions. Specifically Small and Medium sized Enterprises (SME) have disadvantages related to available resources, including no having enough money to invest in equipment and vehicles, to acquire technological resources or to employ trained personnel to manage and maintain distribution and vehicle routing platforms and systems. By the other hand, SMEs distribution activities have special characteristics like usage of vehicles of low capacity and speed and short service time to attend customer requirements. Given specific conditions of SMEs, decision making related with vehicle routing should be supported by quantitative tools fitted to complexity and characteristics of their routing operations. Using a simple insertion heuristic for Split Deliveries Vehicle Routing Problem with Time Windows (SDVRPTW), developed on a common technology platform (Microsoft® Excel™) taking into account SMEs resources restrictions, was validated that SDVRPTW is an appropriate approach for solving SMEs vehicle routing needs over other VRP variants, number of vehicles necessary was reduced about 50% for the study case, as well as was validated that is not necessary additional resources that SMEs already have for modeling their distribution activities using quantitative methods.Maestrí