Manufacturing algebra. Part I: modelling principles and case study

Manufacturing Algebra provides a set of mathematical entities together with composition rules, that are conceived for modeling and controlling a manufacturing system. Here only modeling capabilities are outlined together with a simple case study. The scope is to familiarize the reader with the proposed methodology, and to highlight some peculiarities. Formulation is reduced to a minimum. Among the algebra peculiarities, both manufacturing process and the factory layout are neatly defined in their basic elements, and the link between them is given. A manufacturing model (parts, operations) must include time and space coordinates for being employed by factory elements like Production Units and Control Units. This calls for the definition of event and event sequence. A further peculiarity to be clarified in the second part, is the capability of aggregating algebra elements into higher level components, thus favoring hierarchical description and control of manufacturing system

Control and optimization algorithms for air transportation systems

Modern air transportation systems are complex cyber-physical networks that are critical to global travel and commerce. As the demand for air transport has grown, so have congestion, flight delays, and the resultant environmental impacts. With further growth in demand expected, we need new control techniques, and perhaps even redesign of some parts of the system, in order to prevent cascading delays and excessive pollution. In this survey, we consider examples of how we can develop control and optimization algorithms for air transportation systems that are grounded in real-world data, implement them, and test them in both simulations and in field trials. These algorithms help us address several challenges, including resource allocation with multiple stakeholders, robustness in the presence of operational uncertainties, and developing decision-support tools that account for human operators and their behavior. Keywords: Air transportation; Congestion control; Large-scale optimization; Data-driven modeling; Human decision processe

Оптимизация процесса передачи данных в модели двухфазной системы массового обслуживания

Рассматривается управляемая сеть массового обслуживания типа тандем, включающая две одноканальные системы с конечной очередью и предусматривающая механизм блокировки первого сервера.Первая система принимает нестационарный пуассоновский поток пакетов, обработка которых производится с управляемой скоростью. Если очередь в первой системе переполнена, поступающий пакет теряется. Вторая система не допускает своей перегрузки за счет управления вероятностью приема (ее снижение приводит к замедлению отсылки пакета из первой системы). Данная сеть массового обслуживания описывается управляемым марковским процессом, оптимизация которого проводится на конечном промежутке времени на основе минимизации среднего числа потерь с учетом ограничений на время полного обслуживания и энергозатраты первой системы.Работа выполнена при финансовой поддержке Российского научного фонда (проект № 16-11-00063)

Rate control of a queue with quality-of-service constraint under bounded and unbounded action spaces

We consider a simple Markovian queue with Poisson arrivals and exponential service times for jobs. The controller can choose service rates from a specified action space depending on number of jobs in the queue. The queue has a finite buffer and when full, new jobs get rejected. The controller’s objective is to choose optimal (state-dependent) service rates that minimize a suitable long-run average cost, subject to an upper bound on the job rejection-rate (quality-of-service constraint). We solve this problem of finding and computing the optimal control under two cases: When the action space is unbounded (i.e. [0, ∞)) and when it is bounded (i.e. [0, μ ̄], for some μ ̄ \u3e 0). We also numerically compute and compare the solutions for different specific choices of the cost function

Routing of airplanes to two runways: monotonicity of optimal controls

We consider the problem of routing incoming airplanes to two runways of an airport. Due to air turbulence, the necessary separation time between two successive landing operations depends on the types of the airplanes. When viewed as a queueing problem, this means that we have dependent service times. The aim is to minimise waiting times of aircrafts. We consider here a model where arrivals form a stochastic process and where the decision maker does not know anything about future arrivals. We formulate this as a problem of stochastic dynamic programming and investigate monotonicity of optimal routing strategies with respect e.g. to the workload of the runways. We show that an optimal strategy is monotone (i.e. of switching type) only in a restricted case where decisions depend on the state of the runways only and not on the type of the arriving aircraft. Surprisingly, in the more realistic case where this type is also known to the decision maker, monotonicity need not hold

Order Acceptance and Scheduling: A Taxonomy and Review

Over the past 20 years, the topic of order acceptance has attracted considerable attention from those who study scheduling and those who practice it. In a firm that strives to align its functions so that profit is maximized, the coordination of capacity with demand may require that business sometimes be turned away. In particular, there is a trade-off between the revenue brought in by a particular order, and all of its associated costs of processing. The present study focuses on the body of research that approaches this trade-off by considering two decisions: which orders to accept for processing, and how to schedule them. This paper presents a taxonomy and a review of this literature, catalogs its contributions and suggests opportunities for future research in this area