A Digital Measuring and Load Planning System for Large Transport Assets

Recently, the efforts involved in the digitization and digitalization of logistics processes have grown tremendously. In line with such efforts, we investigate the potential of the process-integrated measuring and load planning of large transport assets. More precisely, considering the case of a German timber processor and retailer, we implement a digital measuring system, which performs precise measuring of regularly shaped wooden assets. The cognitive system uses laser and vision sensors, and measurements can be performed during the asset’s transportation on a forklift. The resulting data can be used to conduct a comprehensive load planning for scheduled delivery tours. The performance of our measurement system is evaluated using a small example dataset of the use case at hand. The a-priori set goal of maximum deviations of 5 cm, 7 cm and 14 cm in height, width and length, respectively, are achieved in 89% of the test cases. The proposed load planning algorithm is integrated in a commercial tour planning service to verify the feasibility of serving several customers within the same tour. We present the method’s applicability to our described use case of integrated measurement and planning

A branch-and-cut algorithm for vehicle routing problems with three-dimensional loading constraints

This paper presents a new branch-and-cut algorithm based on infeasible path elimination for the three-dimensional loading capacitated vehicle routing problem (3L-CVRP) with different loading problem variants. We show that a previously infeasible route can become feasible by adding a new customer if support constraints are enabled in the loading subproblem and call this the incremental feasibility property. Consequently, different infeasible path definitions apply to different 3L-CVRP variants and we introduce several variant-depending lifting steps to strengthen infeasible path inequalities. The loading subproblem is solved exactly using a flexible constraint programming model to determine the feasibility or infeasibility of a route. An extreme point-based packing heuristic is implemented to reduce time-consuming calls to the exact loading algorithm. Furthermore, we integrate a start solution procedure and periodically combine memoized feasible routes in a set-partitioning-based heuristic to generate new upper bounds. A comprehensive computational study, employing well-known benchmark instances, showcases the significant performance improvements achieved through the algorithmic enhancements. Consequently, we not only prove the optimality of many best-known heuristic solutions for the first time but also introduce new optimal and best solutions for a large number of instances.Comment: 33 pages, 13 figures, 7 tables, Submitted to Transportation Scienc

The split delivery vehicle routing problem with three-dimensional loading constraints

 The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints (3L-SDVRP) combines vehicle routing and three-dimensional loading with additional packing constraints. In the 3L-SDVRP splitting deliveries of customers is basically possible, i.e. a customer can be visited in two or more tours. We examine essential problem features and introduce two problem variants. In the first variant, called 3L-SDVRP with forced splitting, a delivery is only split if the demand of a customer cannot be transported by a single vehicle. In the second variant, termed 3L-SDVRP with optional splitting, splitting customer deliveries can be done any number of times. We propose a hybrid algorithm consisting of a local search algorithm for routing and a genetic algorithm and several construction heuristics for packing. Numerical experiments are conducted using three sets of instances with both industrial and academic origins. One of them was provided by an automotive logistics company in Shanghai; in this case some customers per instance have a total freight volume larger than the loading space of a vehicle. The results prove that splitting deliveries can be beneficial not only in the one-dimensional case but also when goods are modeled as three-dimensional items

Diseño de un proceso de logística inversa para la reutilización de botellas de vidrio en el sector cervecero. Caso : cervecería artesanal Moonshine

El calentamiento global es uno de los problemas ambientales más reconocidos en todo el mundo, por lo tanto, sectores industriales como la industria de la cerveza están buscando nuevos enfoques para reducir su impacto de fabricación negativo en el medio ambiente, lo que eventualmente lleva a un desarrollo sostenible. Moonshine, una cervecería artesanal, ha reconocido esta necesidad y es por eso que está interesada en propuestas relacionadas con el proceso de logística inversa que implica la reutilización de las botellas de vidrio que están empleando actualmente. Este proyecto implica un diseño de tres etapas. En primer lugar, se diseñó un proceso de lavado-desinfección para botellas de vidrio. En segundo lugar, se definió un modelo para la distribución y recolección de las rutas de botellas de vidrio, desde los clientes hasta las instalaciones de Moonshine. Por último, para evaluar el impacto de las etapas antes mencionadas, se presenta una medición financiera y ambiental utilizando indicadores tales como costo-beneficio y huella de carbono, respectivamente, lo que facilita la toma de decisiones de Moonshine, en cuanto a si aplicarán la propuesta en el futuro.Global warming Is one of the most recognized environmental issues worldwide, thus, industrial sectors such as the beerindustry are seeking for new approaches to reduce their negative manufacturing ¡mpact on the environment, leadlng eventually to a sustainable development. Moonshlne, a craft brewery, has recognized this need and that is why it is interested in proposals related to reverse logistics process that Implícales the reuse of the glass bottles they are currently using. This project implies a three-stagedesign. Firstly, a washing-disinfection process for glass bottles was designed. Secondly, the definition of distrlbution and recollection of the glassbottles routes, from the customers to Moonshine's facilities, werc established. Lastly, in order to evalúate the ¡mpact of theaforementioned stages.a financial and environmentalmeasuring is presented using indicators such as cost-benefit and carbón footprint, respectively, thus facilitating Moonshine’s decision-making, as to whether they willapply the proposal in the future.Ingeniero (a) IndustrialPregrad

Маршрутизація транспортних засобів з часовими вікнами

Магістерська дисертація: 108 с., 27 рис., 14 табл., 67 джерел. Актуальність. Згідно з 30м щорічним звітом з логістики від The Council of Supply Chain Management Professionals (CSCMP) [1] лише в США за рік було витрачено понад 1.64 трильйонів доларів на логістичні та транспортні операції, а кінцева вартість продукту, що потрапляє до споживача, може складатись до 70% з транспортних витрат. Тож перед галуззю транспортної логістики однією з важливіших задач постає економія ресурсів та мінімізація екологічного сліду при транспортуванні вантажів. Для вирішення цієї проблеми стоїть питання розробки алгоритмів та програмних продуктів, що будуть скорочувати маршрути транспортних засобів. В останні роки значно збільшилась частка персональних доставок, які прив’язанні до зайнятості клієнтів, актуальним є питання врахування часових вподобань одержувачів вантажу. Математичне формулювання цієї задачі відоме як задача маршрутизації транспортних засобів (далі VRP) з урахуванням часових вікон (далі VRPTW), яка накладає певні часові обмеження на обслуговування клієнтів транспортної мережі. Робота присвячена дослідженню та удосконаленню розв’язання задачі VRPTW. Зв'язок роботи з науковими програмами, планами, темами. Робота виконувалась на кафедрі автоматизованих систем обробки інформації та управління Національного технічного університету України «Київський політехнічний інститут ім. Ігоря Сікорського» в рамках теми «Ефективні методи розв'язання задач теорії розкладів» (№ ДР 0117U000919). Мета роботи і завдання дослідження. Метою є підвищення ефективності методів розв’язання задачі маршрутизації транспортних засобів з часовими вікнами. Для досягнення поставленої мети необхідно вирішити такі завдання: -проаналізувати відомі результати розв’язання задачі маршрутизації транспортних засобів; -удосконалити існуючі алгоритми розв’язання задачі маршрутизації транспортних засобів з урахуванням часових вікон за рахунок модифікації та поєднання метаевристик; -розробити програмну реалізацію розроблених алгоритмів; -провести дослідження ефективності розроблених алгоритмів. Об’єкт дослідження – процес організації транспортних перевезень. Предмет дослідження – задача маршрутизації транспортних засобів з часовими вінками. Методи дослідження, застосовані в роботі, базуються на методах дослідження операцій, зокрема на метаевристичних алгоритмах. Наукова новизна отриманих результатів. Розроблені модифікований та гібридний алгоритми розв’язання задачі VRPTW. Публікації. Основні теоретичні та практичні положення викладено в матеріалах VI всеукраїнської науково-практичної конференції молодих вчених та студентів «Інформаційні системи та технології управління» (ІСТУ-2021).Master dissertation: 108 p., 27 fig., 14 tab, 67 sources. The relevance. According to the 30th Annual State of Logistics Report by the Council of Supply Chain Management Professionals (CSCMP) there was spent over 1.64 trillion on logistics and transportation operations in USA [1]. The final costs of the product that reaches the consumer can consist up to 70% of transportation costs. Therefore, one of the most important tasks for the transportation logistics industry is to save resources and minimize the environmental footprint during transportation of goods. To solve this problem, it is necessary to develop algorithms and software products that will decrease the routes of vehicles. In recent years significantly increased the proportion of personal delivery that employment associated with a client topical issue taking into account time preferences consignees. The mathematical formulation of this problem is known as the vehicle routing problem (VRP) with time windows (VRPTW), which imposes certain time constraints on the service of customers. The work is devoted to research and improvement of the VRPTW problem. The work is devoted to the study and improvement of solving VRPTW problem. Relationship of work with scientific programs, plans, themes. The work was done at the department of computer-aided management and data processing systems of the National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute» within the theme «Effective methods for solving problems of scheduling theory» (№ DR 0117U000919). Purpose and objectives of the study. The goal of the research is to is to minimize the total cost of transportation of products to customers in a certain time period. To achieve this goal it is necessary to solve the following tasks: -to analyze known results of solving the Vehicle Routing Problem; -to improve the existing algorithms for solving the problem of vehicle routing considering time windows by modifying and combining metaheuristics; -to develop a software implementation of the developed algorithms; -to conduct research on the effectiveness of the developed algorithms. The object of study – the process organisation of transportation. Purpose of the study – Vehicle Routing Rroblem with Time Windows. Methods used in the paper are based on the methods of operations research, such as metaheuristics algorithms. Scientific novelty. New modified and hybrid algorithms developed for solving VRPTW. Publications. The results of the research were published in the materials of VI Ukrainian scientific and practical conference of young scientists and students "Information Systems and Management Technologies" (ISTU-2021)

Оптимізація маршрутів безпілотних літальних апаратів за наявності декількох депо

Магістерська дисертація: 110 с., 33 рис., 44 табл., 55 джерел, 1 додаток. Актуальність. У сучасному світі задачі маршрутизації транспортних засобів відіграють ключову роль у логістиці та інших застосуваннях. Це пов’язано з постійним збільшенням продукції на ринку та потребою в доставці великого обсягу товарів за малий час та з мінімальними витратами. Якщо раніше в якості транспортних засобів розглядали наземний транспорт, то нині стрімко набувають популярності безпілотні літальні апарати. Уже зараз їх почали розглядати не лише як засоби доставки товарів, а і як транспорт, який може дістатися до складнодоступних місць. Безпілотні літальні апарати значно скорочують витрати коштів та часу, що необхідні для обстеження та/чи обслуговування об’єктів, оскільки є дешевшими в експлуатації за традиційні транспортні засоби та можуть швидко дістатися до необхідних об’єктів. Зв’язок роботи з науковими програмами, планами, темами. Робота виконувалась на кафедрі автоматизованих систем обробки інформації та управління Національного технічного університету України «Київський політехнічний інститут імені Ігоря Сікорського» в рамках теми Інституту кібернетики ім. В. М. Глушкова НАН України (2017–2021 рр.): ВФ.180.11 «Розробити математичний апарат, орієнтований на створення інтелектуальних інформаційних технологій розв’язування проблем комбінаторної оптимізації та інформаційної безпеки» (№ 0117U000323). Мета роботи – мінімізація часу обстеження або вартості маршрутів внаслідок обстеження та/чи обслуговування заданої множини цілей на місцевості безпілотними літальними апаратами, що можуть розміщуватися в декількох депо, за наявності певних додаткових обмежень. Для досягнення мети необхідно виконати наступні завдання: виконати аналіз сучасного стану задач маршрутизації транспортних засобів та задач маршрутизації для безпілотних літальних апаратів; здійснити огляд наявних методів розв’язування задач маршрутизації транспортних засобів за наявності декількох депо; розробити алгоритми розв’язування задачі маршрутизації безпілотних літальних апаратів за наявності декількох депо (детермінований локальний пошук, пошук із заборонами, алгоритм імітації відпалу, алгоритм прискореного ймовірнісного моделювання); розробити програмне забезпечення; виконати дослідження ефективності розроблених алгоритмів. Об’єктом дослідження роботи є процес побудови маршрутів за допомогою безпілотних літальних апаратів. Предметом дослідження є методи побудови маршрутів за наявності декількох депо. Методи дослідження – емпіричні та теоретичні. Наукова новизна – класифікація задач маршрутизації транспортних засобів, розробка нових алгоритмів маршрутизації безпілотних літальних апаратів за наявності декількох депо. Прикладна значущість. Методи та програмне забезпечення можуть бути використані для розв’язування задач маршрутизації безпілотних літальних апаратів за наявності декількох депо в таких галузях, як пошукові та порятункові роботи, сільське господарство, моніторинг навколишнього середовища, воєнна справа, картографія, логістика. Публікації. Матеріали роботи опубліковані в фаховому журналі категорії Б «Науковий вісник Ужгородського університету. Серія математика й інформатика» [1] та на VІ Всеукраїнській науково-практичній конференції молодих вчених та студентів «Інформаційні системи та технології управління» (ІСТУ-2021, м. Київ).Master's dissertation: 110 pages, 33 figures, 44 tables, 55 ​​sources, 1 appendix. Topicality. In today's world, vehicle routing tasks play a key role in logistics and other applications. This is due to the constant increase in production on the market and the need to deliver a large volume of goods in a short time and with minimal costs. If previously ground vehicles were considered as vehicles, now unmanned aerial vehicles are rapidly gaining popularity. They have already begun to be seen not only as a means of delivering goods, but also as a means of transport that can reach hard-to-reach places. Unmanned aerial vehicles significantly reduce the cost and time required to inspect and / or maintain facilities, as they are cheaper to operate than traditional vehicles and can quickly reach the required facilities. Connection of work with scientific programs, plans, themes. The work was performed at the Department of Automated Information Processing and Control Systems of the National Technical University of Ukraine “Kyiv Polytechnic Institute named after Igor Sikorsky” within the theme of the Institute of Cybernetics named after Victor Glushkov NAS of Ukraine (2017–2021): VF.180.11 “To develop a mathematical apparatus focused on the creation of intelligent information technologies for solving problems of combinatorial optimization and information security” (№ 0117U000323). The purpose of the work is to minimize the time of inspection or the cost of routes due to the inspection and / or maintenance of a given set of targets in the field by unmanned aerial vehicles that can be located in several depots, subject to certain additional restrictions. To achieve this purposes you must perform the following tasks: perform an analysis of the current state of vehicle routing tasks and routing tasks for unmanned aerial vehicles; to review the existing methods of solving vehicle routing problems in the presence of several depots; to develop algorithms for solving the problem of routing unmanned aerial vehicles in the presence of several depots (deterministic local search, search with prohibitions, annealing simulation algorithm, algorithm of accelerated probabilistic modeling); develop software; perform research on the effectiveness of the developed algorithms. The object of the study is the process of building routes using unmanned aerial vehicles. The subject of research is methods of construction of routes in the presence of several depots. Research methods – empirical and theoretical. Scientific novelty – classification of routing tasks of vehicles, development of new algorithms for routing unmanned aerial vehicles in the presence of several depots. Applied significance. Methods and software can be used to solve the problems of routing unmanned aerial vehicles in the presence of several depots in areas such as search and rescue, agriculture, environmental monitoring, military affairs, cartography, logistics. Publications. Materials of the work were published in the professional journal category B “Scientific Bulletin of Uzhgorod University. Mathematics and Informatics Series” [1] and at the VI All-Ukrainian Scientific and Practical Conference of Young Scientists and Students “Information Systems and Management Technologies” (ISTU-2021, Kyiv)

Optimal Design and Operation of WHO-EPI Vaccine Distribution Chains

Vaccination has been proven to be the most effective method to prevent infectious diseases and in 1974 the World Health Organization (WHO) established the Expanded Programme on Immunization (EPI) to provide universal access to all important vaccines for all children, with a special focus on underserved low- and middle-income countries. However, there are still roughly 20 million infants worldwide who lack access to routine immunization services and remain at risk, and millions of additional deaths could be avoided if global vaccination coverage could improve. The broad goal of this research is to optimize the design and operation of the WHO-EPI vaccine distribution chain in these underserved low- and middle-income countries. We first present a network design problem for a general WHO-EPI vaccine distribution network by developing a mathematical model that formulates the network design problem as a mixed integer program (MIP). We then present three algorithms for typical problems that are too large to be solved using commercial MIP software. We test the algorithms using data derived from four different countries in sub-Saharan Africa and show that with our final algorithm, high-quality solutions are obtained for even the largest problems within a few minutes. We then discuss the problem of outreach to remote population centers when resources are limited and direct clinic service is unavailable. A set of these remote population centers is chosen, and over an appropriate planning period, teams of clinicians and support personnel are sent from a depot to set up mobile clinics at these locations to vaccinate people there and in the immediate surrounding area. We formulate the problem of designing outreach efforts as an MIP that is a combination of a set covering problem and a vehicle routing problem. We then incorporate uncertainty to study the robustness of the worst-case solutions and the related issue of the value of information. Finally, we study a variation of the outreach problem that combines Set Covering and the Traveling Salesmen Problem and provides an MIP formulation to solve the problem. Motivated by applications where the optimal policy needs to be updated on a regular basis and where repetitively solving this via MIP can be computationally expensive, we propose a machine learning approach to effectively deal with this problem by providing an opportunity to learn from historical optimal solutions that are derived from the MIP formulation. We also present a case study on outreach operations and provide numerical results. Our results show that while the novel machine learning based mechanism generates high quality solution repeatedly for problems that resemble instances in the training set, it does not generalize as well on a different set of optimization problems. These mixed results indicate that there are promising research opportunities to use machine learning to achieve tractability and scalability

A biased-randomized iterated local search for the vehicle routing problem with optional backhauls

[EN] The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional-but subject to a penalty cost. Both transportation costs and penalties associated with non-collecting decisions are considered. A mixed-integer linear model is proposed and solved for small instances. Also, a metaheuristic algorithm combining biased randomization techniques with iterated local search is introduced for larger instances. Our approach yields cost savings and is competitive when compared to other state-of-the-art approaches.This work has been partially supported by COLCIENCIAS - Colombia, the School of Industrial Engineering of Universidad del Valle, the IoF2020, the AGAUR (2018-LLAV-00017), and the Erasmus+ Program (2018-1-ES01-KA103-049767). We also acknowledge the support of the doctoral programs at the Universitat Oberta de Catalunya and the Universidad de La Sabana.Londoño, JC.; Tordecilla, RD.; Do C. Martins, L.; Juan, AA. (2021). A biased-randomized iterated local search for the vehicle routing problem with optional backhauls. Top. 29(2):387-416. https://doi.org/10.1007/s11750-020-00558-x387416292Al Chami Z, El Flity H, Manier H, Manier MA (2018) A new metaheuristic to solve a selective pickup and delivery problem. In: 2018 4th international conference on logistics operations management (GOL), IEEE, pp 1–5Arab R, Ghaderi S, Tavakkoli-Moghaddam R (2018) Bi-objective inventory routing problem with backhauls under transportation risks: two meta-heuristics. Transportation Letters, pp 1–17Assis LP, Maravilha AL, Vivas A, Campelo F, Ramírez JA (2013) Multiobjective vehicle routing problem with fixed delivery and optional collections. 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