Common Due Date Assignment to Minimize Total Penalty for the One Machine Scheduling Problem

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

doi:10.1287/opre.30.2.391

Cited by 381 publications

(142 citation statements)

References 0 publications

Supporting

Mentioning

140

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

Section: Order Due-date Assignmentmentioning

confidence: 99%

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

2016

View full text Add to dashboard Cite

show abstract

“…In [75], β j = β, γ j = γ and α j = α; in [3], β j = β, γ j = γ and α j = 0; in [21], β j = γ j = w j and α j = 0; in [24], β j = γ j = w j and α j = α. In this problem, it is easy to show that the optimal due date d is equal to the completion time of some job j * , i.e., d = C j * .…”

Section: Equal Order Arrival Timesmentioning

confidence: 99%

Due Date Management Policies

Keskinocak

Tayur

2004

International Series in Operations Research &Amp; Management Science

View full text Add to dashboard Cite

“…and this objective function has been studied by, for example, Panwalkar et al (1982), Emmons (1987), and Bagchi et al (1987). The objective function arising in the case new, cdd, ns (and cpt or ncpt) has been studied, for example, by Ahmed and Sundararaghavan (1990), Cheng (1987), Emmons (1987), Ouaddus (1987), Bector et al (1988), Baker and Scudder (1989), Hall and Posner (1991), and Hoogeveen and van de Velde (1991).…”

Section: =1 1=1mentioning

confidence: 99%

On the Meaningfulness of Optimal Solutions to Scheduling Problems: Can an Optimal Solution be Nonoptimal?

Mahadev

Pekec

Roberts

1998

Operations Research

View full text Add to dashboard Cite

We consider the problem of finding an optimal schedule for jobs on a single machine when there are penalties for both tardy and early arrivals. We point out that if attention is paid to how these penalties are measured, then a change of scale of measurement might lead to the anomalous situation where a schedule is optimal if these parameters are measured in one way, but not if they are measured in a different way that seems equally acceptable. In particular, we note that if the penalties measure utilities or disutilities, or loss of goodwill or customer satisfaction, then these kinds of anomalies can occur, for instance if we change both unit and zero point in scales measuring these penalties. We investigate situations where problems of these sorts arise for four specific penalty functions under a variety of different assumptions. The results of the paper have implications far beyond the specific scheduling problems we consider, and suggest that considerations of scale of measurement should enter into analysis of conclusions of optimality both in scheduling problems and throughout combinatorial optimization.M any practical problems involve the search for an optimal schedule. We consider the problem of scheduling n jobs on a single machine in which each job has a specified due date or completion time and a penalty is applied for a completion time different from the desired one. In many practical problems, a penalty is applied only for tardy completions; while more generally, a penalty is applied to both early and tardy completions, perhaps in a different way. The interest in scheduling problems where penalties are applied to early arrivals as well as late arrivals is closely tied to the concept of "just-in-time" production, the goal being to have "the right amount of materials of the right quality at the right time in the right place to produce the right quantity of items demanded by the next step of the production" (Cheng 1990). Because penalties can be applied to early arrivals, we allow the machine to lie idle and we schedule without preemption, i.e., we do not allow a job to be interrupted once it is started. The penalties we study involve weighting factors that weight the deviations from desired completion times.Often these weights are not uniquely determined. For instance, two weight assignments may be equally acceptable if they both give rise to the same ordering of the items or if one is related to the other by a change of scale. Typically weights are measured using some scale of measurement, and we examine the effect on the solution to a scheduling problem if we make admissible changes of scale. We show that in some cases such changes can transform an optimal solution into a nonoptimal one, and we systematically describe those situations when this anomaly occurs. More precisely, we show that the conclusion of optimality can be meaningless in a technical sense that we shall make precise. The main point of this paper is to show that considerations of scale change need to play a role in analysis of scheduli...

show abstract

Common Due Date Assignment to Minimize Total Penalty for the One Machine Scheduling Problem

Cited by 381 publications

References 0 publications

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

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

Due Date Management Policies

On the Meaningfulness of Optimal Solutions to Scheduling Problems: Can an Optimal Solution be Nonoptimal?

Contact Info

Product

Resources

About