Мінімізація сумарного зваженого запізнення завдань із спільним директивним строком на паралельних приладах для випадку узгоджених ваг і тривалостей

We consider n tasks scheduling problem on m identical parallel machines by the criterion of minimizing the total weighted tardiness of tasks. All tasks arrive for processing at the same time. Weights and processing times are agreeable, that is, a greater weight of a task corre sponds to a shorter processing time. In addition, we have arbitrary start times of machines for tasks processing. The times may be less or greater than the due date or to coincide with it. The problem in this formulation is addressed for the first time. It can be used to provide planning and decision making in systems with a network representation of technological processes and limited resources. We give efficient PSC-algorithm with ( log ) complexity that includes the polynomial component and the approximation algorithm based on permutations of tasks. The polynomial component contains sufficient signs of optimality of the obtained solutions and allows to obtain an exact solution by polynomial subalgorithm. In the case when the sufficient signs of optimality do not fulfill, we obtain approximate solution with an estimate of deviation from the optimum for each individual problem instance of any practical dimension. We show that a schedule obtained as a result of the problem solving can be split into two schedules: the schedule on machines which start time is less than or equal to the due date, and the schedule on machines which start after the due date. Optimization is only done in the first schedule. The second schedule is optimal by construction. Statistical studies of the PSC-algorithm showed its high efficiency. We solved problems with dimensions up to 40,000 tasks and up to 30 machines. The average time to solve the problem by the algorithm using the most efficient types of permutations was 27.3 ms for this dimension. The average frequency of an optimal solution obtaining amounted to 90.3 %. The average deviation from an optimum was no more than 0.000251.Розглядається задача складання розкладів виконання n завдань на m ідентичних паралельних приладах за критерієм мінімізації сумарного зваженого запізнення завдань. Всі завдання надходять на обслуговування одночасно. Ваги і тривалості узгоджені, тобто завданню з меншою тривалістю відповідає більша вага. Додатково, задані довільні моменти початку роботи приладів на виконання завдань, які можуть бути як менше директивного строку, так і більше, або співпадати з ним. У такій постановці задача розв'язується вперше. Вона може використовуватися для забезпечення планування та прийняття рішень в системах з мережним представленням технологічних процесів та обмеженими ресурсами. Наведено ефективний ПДС-алгоритм її розв'язання із трудомісткістю ( log ), який включає поліноміальну складову з достатніми ознаками оптимальності одержуваних розв'язків, яка дозволяє отримувати точний розв'язок поліноміальним підалгоритмом. У разі невиконання достатніх ознак оптимальності ми отримуємо наближений розв'язок з оцінкою відхилення отриманого розв'язку від оптимального для кожної індивідуальної задачі будь-якої практичної розмірності. Показано, що розклад, отриманий в результаті розв'язання задачі, можна умовно розбити на два розклади – розклад на приладах, момент початку роботи яких менше або дорівнює директивному строку, та розклад на приладах, що починають роботу після директивного строку. Оптимізація виконується тільки у першому розкладі. Другий розклад оптимальний за побудовою. Статистичні дослідження ПДС-алгоритму показали його високу ефективність. Розв'язувались задачі з розмірністю до 40 000 завдань з числом приладів до 30. Середній час розв'язання задачі алгоритмом, що використовує найбільш ефективні типи перестановок, склав 27,3 мс при цій розмірності. Середня частота отримання оптимального розв'язку склала до 90,3 %. Середнє відхилення від оптимуму – не більш, ніж 0,000251

A fast FPTAS for single machine scheduling problem of minimizing total weighted earliness and tardiness about a large common due date

We address the single machine scheduling problem to minimize the total weighted earliness and tardiness about a nonrestrictive common due date. This is a basic problem with applications to the just-in-time manufacturing. The problem is linked to a Boolean programming problem with a quadratic objective function, known as the half-product. An approach to developing a fast fully polynomial-time approximation scheme (FPTAS) for the problem is identified and implemented. The running time matches the best known running time for an FPTAS for minimizing a half-product with no additive constan

Serial-batch scheduling – the special case of laser-cutting machines

The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning

Single-machine scheduling with stepwise tardiness costs and release times

We study a scheduling problem that belongs to the yard operations component of the railroad planning problems, namely the hump sequencing problem. The scheduling problem is characterized as a single-machine problem with stepwise tardiness cost objectives. This is a new scheduling criterion which is also relevant in the context of traditional machine scheduling problems. We produce complexity results that characterize some cases of the problem as pseudo-polynomially solvable. For the difficult-to-solve cases of the problem, we develop mathematical programming formulations, and propose heuristic algorithms. We test the formulations and heuristic algorithms on randomly generated single-machine scheduling problems and real-life datasets for the hump sequencing problem. Our experiments show promising results for both sets of problems

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

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

An exact extended formulation for the unrelated parallel machine total weighted completion time problem

The plethora of research on NP-hard parallel machine scheduling problems is focused on heuristics due to the theoretically and practically challenging nature of these problems. Only a handful of exact approaches are available in the literature, and most of these suffer from scalability issues. Moreover, the majority of the papers on the subject are restricted to the identical parallel machine scheduling environment. In this context, the main contribution of this work is to recognize and prove that a particular preemptive relaxation for the problem of minimizing the total weighted completion time (TWCT) on a set of unrelated parallel machines naturally admits a non-preemptive optimal solution and gives rise to an exact mixed integer linear programming formulation of the problem. Furthermore, we exploit the structural properties of TWCT and attain a very fast and scalable exact Benders decomposition-based algorithm for solving this formulation. Computationally, our approach holds great promise and may even be embedded into iterative algorithms for more complex shop scheduling problems as instances with up to 1000 jobs and 8 machines are solved to optimality within a few seconds

A single-machine scheduling problem with multiple unavailability constraints: A mathematical model and an enhanced variable neighborhood search approach

AbstractThis research focuses on a scheduling problem with multiple unavailability periods and distinct due dates. The objective is to minimize the sum of maximum earliness and tardiness of jobs. In order to optimize the problem exactly a mathematical model is proposed. However due to computational difficulties for large instances of the considered problem a modified variable neighborhood search (VNS) is developed. In basic VNS, the searching process to achieve to global optimum or near global optimum solution is totally random, and it is known as one of the weaknesses of this algorithm. To tackle this weakness, a VNS algorithm is combined with a knowledge module. In the proposed VNS, knowledge module extracts the knowledge of good solution and save them in memory and feed it back to the algorithm during the search process. Computational results show that the proposed algorithm is efficient and effective