Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Kanet, John J.; Sridharan, V.

doi:10.1287/opre.48.1.99.12447

Cited by 129 publications

(64 citation statements)

References 47 publications

(68 reference statements)

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“…Note that, differently from the problem considered in [10,20,21], in the present work, the insertion of idle time in the schedule can be advantageous. See [6] for a literature review about scheduling with inserted idle time.…”

Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Ronconi

Birgin

2011

Just-in-Time Systems

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Scheduling problems involving both earliness and tardiness costs have received significant attention in recent years. This type of problem became important with the advent of the justin-time (JIT) concept, where early or tardy deliveries are highly discouraged. In this work we examine the flowshop scheduling problem with no storage constraints and with blocking inprocess. In this latter environment, there are no buffers between successive machines; therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Performance is measured by the minimization of the sum of earliness and tardiness of the jobs. Mixed-integer models that represent these scheduling flowshop problems are presented. The models are evaluated and compared in several problems using commercial known software.

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Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Ronconi

Birgin

2011

Just-in-Time Systems

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“…We call this artificial delay policy strategic delay, because its rationale is to manipulate customers' strategic service class choices, and its operational impact is that scheduling is no longer work conserving. Strategic delay increases the delay cost, which sets it apart from standard instances of optimal server idleness (see Kanet and Sridharan 2000). The value of strategic delay can be significant.…”

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confidence: 99%

Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay

Afèche

2013

M&SOM

162

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H ow should a firm design a price/lead-time menu and scheduling policy to maximize revenues from heterogeneous time-sensitive customers with private information about their preferences? We consider this question for a queueing system with two customer types and provide the following results. First, we develop a novel problem formulation and solution method that combines the achievable region approach with mechanism design. This approach extends to menu design problems for other systems. Second, the work conserving c priority rule, known to be delay cost minimizing, incentive-compatible, and socially optimal, need not be revenue maximizing. A strategic delay policy may be optimal: It prioritizes impatient customers, but artificially inflates the lead times of patient customers. This suggests a broader guideline: Revenue-maximizing firms that lack customer-level demand information should also consider customer incentives, not only operational constraints, in their scheduling policies. Third, we identify general necessary and sufficient conditions for optimal strategic delay: a price, a lead-time, and a segment-size condition. We translate these into demand and capacity parameter conditions for cases with homogeneous and heterogeneous valuations for each type. In some cases strategic delay is optimal if capacity is relatively abundant, in others if it is relatively scarce.

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“…The difficult combinatorial structure of machine scheduling problems stems from the first phase, while the second phase -also referred to as the optimal timing problem -is a simple optimization problem for many important machine scheduling problems. On a single machine, the optimal timing problem is trivial for regular performance measures, such as TWCT and TWT , which are non-decreasing in the completion times, and it can often be solved by a low-order polynomial time algorithm or as a linear programming problem for non-regular performance measures (Kanet and Sridharan, 2000). Moreover, a feasible job processing sequence can be expressed as an assignment (Keha et al, 2009), and for any assignment and performance measure the optimal job completion times and the resulting value of the performance measure can be identified by solving an appropriate optimal timing problem.…”

Section: Underlying Deterministic Modelmentioning

confidence: 99%

Minimizing value-at-risk in single-machine scheduling

2016

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The vast majority of the machine scheduling literature focuses on deterministic problems in which all data is known with certainty a priori. In practice, this assumption implies that the random parameters in the problem are represented by their point estimates in the scheduling model. The resulting schedules may perform well if the variability in the problem parameters is low. However, as variability increases accounting for this randomness explicitly in the model becomes crucial in order to counteract the ill effects of the variability on the system performance. In this paper, we consider single-machine scheduling problems in the presence of uncertain parameters. We impose a probabilistic constraint on the random performance measure of interest, such as the total weighted completion time or the total weighted tardiness, and introduce a generic risk-averse stochastic programming model. In particular, the objective of the proposed model is to find a non-preemptive static job processing sequence that minimizes the value-at-risk (VaR) of the random performance measure at a specified confidence level. We propose a Lagrangian relaxation-based scenario decomposition method to obtain lower bounds on the optimal VaR and provide a stabilized cut generation algorithm to solve the Lagrangian dual problem. Furthermore, we identify promising schedules for the original problem by a simple primal heuristic. An extensive computational study on two selected performance measures is presented to demonstrate the value of the proposed model and the effectiveness of our solution method.

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Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Cited by 129 publications

References 47 publications

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay

Minimizing value-at-risk in single-machine scheduling

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