Optimal assignment of due-dates for a single processor scheduling problem

Seidmann, Abraham; Panwalkar, S. S.; Smith, Milton L.

doi:10.1080/00207548108956667

Cited by 173 publications

(53 citation statements)

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“…Among the most significant contributions, Cheng and Gupta [48] review due-date assignment approaches up to 1990, whereas Gordon et al [46] review more recent publications (up to 2002). In most works, the due-date assignment problem is treated using benchmarking instances [49], single-resource problems [50,51] or is focused on assembly shops [52]. Moreover, the calculation of due dates in ETO environments is relatively mistreated.…”

Section: Order Due-date Assignmentmentioning

confidence: 99%

A mobile application for knowledge-enriched short-term scheduling of complex products

2016

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The ever-increasing product complexity, especially for the case of engineer-to-order products, highly affects the performance of manufacturing systems. Therefore, a high degree of flexibility is needed during daily decision-making activities, such as production scheduling. For addressing this challenge, this research work proposes a knowledge-enriched short-term job-shop scheduling mechanism, which is implemented into a mobile application. More precisely, it focuses on the short-term scheduling of the resources of the machine shop, through an intelligent algorithm that generates and evaluates alternative assignments of resources to tasks. Based on the requirements of a new order, a similarity mechanism retrieves successfully executed past orders together with a dataset that includes the processing times, the job and task sequence, and the suitable resources. In addition to that, the similarity mechanism is used to calculate the due-date assignments of the orders based on the knowledge stored in past cases. Afterwards, it adapts these parameters to the requirements of the new order so as to evaluate the alternative schedules and identify a good alternative in a timely manner. The deriving schedule can be presented on mobile devices, and it can be manipulated by the planner on-thefly respecting tasks precedence constraints and machine availability. A case study from the mould-making industry is used for validating the proposed method and application.

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Section: Order Due-date Assignmentmentioning

confidence: 99%

A mobile application for knowledge-enriched short-term scheduling of complex products

2016

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“…For these simplified models, a variety of polynomial algorithms have been developed (see, for example, Brucker [4], Kahlbacher [15], Panwalkar et al. [25], Hall and Posner [13], Seidmann et al [28], and Chand and Chhajed [6]); however, these results don't extend in an obvious way to more complex models.…”

Section: Introductionmentioning

confidence: 99%

Combined make-to-order/make-to-stock supply chains

Kaminsky

Kaya

2009

IIE Transactions

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We consider a multi-item manufacturer served by a single supplier in a stochastic environment. The manufacturer and the supplier have to decide which items to produce to stock and which to produce to order. The manufacturer also has to quote due dates to arriving customers for make-to-order products.The manufacturer is penalized for long lead times, missing the quoted lead times and high inventory levels. We consider several variations of this problem, and design effective heuristics for the make-toorder/make-to stock decision, and to find the appropriate inventory levels for make-to-stock items. We also develop scheduling and lead time quotation algorithms for centralized and decentralized versions of the model. We perform extensive computational testing to assess the effectiveness of our algorithms, and to compare the centralized and decentralized models in order to quantify the value of centralized control in this supply chain. As centralized control is not always practical or cost-effective, we explore the value of limited information exchange for this system.

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“…A related problem, where customers have a common preferred due date A, is studied in [86]. A lead time penalty is charged for lead time (or due date) delay, A j = max{0, d j − A}, which is the amount of time the assigned due date of a job exceeds the preferred due date, A.…”

Section: Equal Order Arrival Timesmentioning

confidence: 99%

“…Seidmann and Smith [87] consider the CON due date policy in a multi-machine environment under the objective of minimizing the weighted sum of earliness, tardiness and lead time penalty (the same objective function is also considered in [86]). They assume that the shop is using a priority discipline for sequencing, such as FCFS or EDD, and the probability distribution of the ßow time is known and is common to all jobs.…”

Section: Choosing the Parameters Of Due Date Rulesmentioning

confidence: 99%

“…There are two approaches for resolving this conßict: (1) use an objective function that combines the objectives of both decisions, (2) consider the objective of one decision and impose a constraint on the other decision. A relatively small number of papers follow the Þrst approach [11] [24] [67] [87] [86] using an objective function that is the weighted sum of earliness, tardiness and lead times, where the weights reßect the relevant importance of short lead times vs. meeeting them on time. Among the papers that follow the second approach, some try to achieve due date tightness subject to a service level constraint, while others consider a service objective (e.g., minimizing tardiness) subject to a constraint on minimum due date tightness.…”

Section: Objectives Of Due Date Managementmentioning

confidence: 99%

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