Моделирование цепей поставок

«Мы разрабатываем интегрированную модель оптимизации загрузки и маршрутизации решений исходящей от поставщика цепи поставок автозапчастей. Три вида транспорта, динамический спрос и ограниченные запасы - вот некоторые сложные аспекты. Мы разделяем проблему на две подзадачи, связанные с распределением клиентов по кластерам и маршрутизацией клиентов. Алгоритм запускается ежедневно с различными правилами отправки. Результаты показывают влияние местоположений клиента, запасов и сроков на исходящие затраты на логистику». "We develop an integrated model to optimize loading and routing decisions of an auto-parts supplier's outbound supply chain. Three transportation modes, dynamic demands, and limited inventory are some challenging aspects. We decompose the problem into two sub-problems involving assignment of customers into clusters and routing customers. The algorithm is run daily with varying dispatch rules. The results show the impact of customer locations, inventories, and due dates on outbound logistics costs".

В этой работе оцениваются различные системы межтерминального транспорта (ITT) для порта Роттердам. Власти порта изучают возможные решения для перевозки контейнеров между терминалами на существующих так называемых площадях Маасфлакте-1 и новой площади Маасфлакте-2 в порту. Представлена модель имитации дискретного события, которая включает моделирование трафика, а это означает, что задержки, возникающие из-за трафика, будут влиять на производительность системы. Модель применима к четырём различным транспортным средствам ITT, включая автоматизированные транспортные средства (AGVs), автоматические подъемные механизмы (ALVs), многоприводные системы (MTSs) и сочетание барж и грузовиков. Кроме того, используются три реалистичных сценария возможного спроса для 2030 года. In this paper, various Inter Terminal Transport (ITT) systems for the Port of Rotterdam are evaluated. The Port Authority is investigating possible solutions for the transport of containers between terminals at the existing so-called Maasvlakte 1 and new Maasvlakte 2 areas within the port. A discrete event simulation model is presented that incorporates traffic modeling, which means that delays occurring due to traffic will have an impact on the system's performance. The model is applied to four different ITT vehicle configurations, including Automated Guided Vehicles (AGVs), Automated

Юлия Тропина, консультант The AnyLogic Company, представила доклад "Использование имитационного моделирования для обоснования выбора портового оборудования на примере внутрипортовой логистики". В докладе описан пример использования имитационного моделирования для принятия решения о выборе портового оборудования. Пример основан на реальном проекте, разработанном для французского порта Гавра. В проекте выполнено сравнение двух вариантов оборудования для организации внутрипортовой логистики: традиционных подвижных составов и составов, состоящих из автономных групп вагонов. По результатам проекта руководством порта был сделан обоснованный выбор оптимального оборудования.

Имитационное моделирование как инструмент проектирования инфраструктуры терминально-логистического центра Белый Раст

Демонстрация возможностей IBM Decision Optimization Center 3.9

ИМИТАЦИОННАЯ МОДЕЛЬ СКЛАДА ПРОМЫШЛЕННОГО ПРЕДПРИЯТИЯ ПО ПРОИЗВОДСТВУ БЕТОНА

Пример имитационной модели для анализа вариантов устранения заторов транспортных средств в порту Chennai

Применение имитационного моделирования в Anylogic для оптимизации складских процессов фармацевтической компании. Видео с конференции Anylogic 2013

"We describe a software application that enables owners of generation output from a virtualized Federal Columbia River Power System to safely operate the system while also shaping the generation to meet their energy and economic needs. The application, known colloquially as The Optimizer, employs modern Operations Research techniques to convert a highly non-linear problem into a linear one so as to create a robust solution for the entire, six-dam system on an hourly basis; over a ten-day time horizon; within seconds to minutes. The tool permits two operators to manage and optimize the entire generation portfolios for nine utilities simultaneously in a very stringent time frame around the clock, and enables planners to ensure that the operation of the river meets all of the requirements for flood control, fish management, electrical reliability, safe dam operation, and recreation under high degrees of uncertainty. As a result, the Optimizer allows utilities to integrate renewable, environmentally friendly wind and solar generation into their resource portfolio with hydro generation and empowers fast decision making and adaptation to rapidly changing conditions."

"We partnered with the online flash sales retailer Rue La La to develop and implement a pricing decision support tool that sets initial prices for new products. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time discounts (typically 2-3 days) on designer apparel and accessories. Our approach is two-fold and begins with developing a demand prediction model for new products. The two biggest challenges faced when building our demand prediction model include estimating lost sales due to stockouts, and predicting demand for styles that have no historical sales data. We use descriptive analytics (clustering) and predictive analytics (regression) to address these challenges and predict future demand. Regression trees - an intuitive, yet non-parametric regression model - prove to be effective predictors of demand."

"Ingram Micro, the world's largest technology distributor operates in a high volume low margin environment. The company started its Business Intelligence & Analytics practice in North America (NA) about 6 years ago. Since then the group has built and deployed a scalable highly innovative price optimization engine, imprime™, for NA's $8B spot business, a set of analytics apps, imsmart™ for its internal sales organization and an integrated digital marketing platform, intelligence.ingrammicro.com, to run data-driven marketing campaigns to its customers and end customers. Since 2011, these products and analytical programs have yielded a cumulative benefit of $1.12 Billion of incremental product revenue and $28M of incremental gross profit. These solutions have been effective in driving profitable growth and are scalable. Our next steps are to continue to drive these best practices within the other regions outside NA and continue our sales enablement activities."

"The planning of spare engines and engine parts is a challenging and important task for airlines to seamlessly support flying and engine repair operations. Engines are expensive and critical assets that make this problem important from the financial and operational perspectives. In this talk, we present an application of a simulation-based approach utilized for planning the ownership level of spare engines and engine parts required to achieve a target service level or out-of-service (OTS) aircraft performance metrics. Our application considers both single and multi-location settings as well as two levels of modeling: a higher level where the repairable components are the engines as a whole, and a lower level that focuses on the repair of the individual engine parts. "

"The Mayo Clinic Department of Orthopedic Surgery was facing low utilization of their operating rooms (ORs) for spine surgical procedures, combined with fluctuating empty days and days with overtime to complete scheduled surgeries. Extremely long days ended up being unsafe days with increased provider fatigue and higher likelihood of errors. Investigation revealed the cause to be inaccurate estimation of surgical and non-surgical duration and scheduling of surgeries rather than limited surgery demand. Existing scheduling optimization research in the literature was inadequate, as they provided a single "optimal" solution. Often, the single optimal solution was not satisfactory to the patients and the providers. The team 1) conducted descriptive research using historical data to identify clinical and operational factors; 2) developed and implemented predictive models for the duration of surgical and nonsurgical times in the OR based on these factors; and 3) developed and implemented a prescriptive scheduling search algorithm that suggests multiple slots for a given surgery thereby providing flexibility while ensuring high probability of completion of surgical day without much overtime (completion closer to 5 pm)."

"Long term infrastructure planning of locomotive service facilities is vital to the efficiency of the railroad. We developed a large-scale optimization model that integrates decisions on (i) location, capability, and capacity of fixed facilities, (ii) home location and routing plan of movable facilities, and (iii) assignment of a variety of service demands. A decomposition-based solution framework was developed and shown to bring significant economic benefits in full-scale implementations."

"We present the problem of scheduling crash tests for new vehicle programs at Ford. We developed a completely custom-made scheduling system that transforms a labor-intensive scheduling process relying on high levels of expertise, to a more automated one that utilizes optimization and institutionalizes expert knowledge. Our system enables engineers and managers to consider multiple scheduling scenarios, using efficient interfaces to specify problem instances and efficient methods to solve them."

Статья об имитационном моделировании цепей поставок с использованием гибридного подхода, сочетающего дискретно-событийную модель и модель системной динамики, на примере реально существующей цепи поставок высокой сложности.

Вебинар Д.А. Гаврилова - управление запасами в цепи поставок