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

04231 Abstracts Collection -- Scheduling in Computer and Manufacturing Systems

During 31.05.-04.06.04, the Dagstuhl Seminar 04231 "Scheduling in Computer and Manufacturing Systems" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Flowshop scheduling problems with due date related objectives: A review of the literature

3rd International Conference on Industrial Engineering and Industrial Management XIII Congreso de Ingeniería de Organización Barcelona-Terrassa, September 2nd-4th 200

Stochastic scheduling and workload allocation : QoS support and profitable brokering in computing grids

Abstract: The Grid can be seen as a collection of services each of which performs some functionality. Users of the Grid seek to use combinations of these services to perform the overall task they need to achieve. In general this can be seen as aset of services with a workflow document describing how these services should be combined. The user may also have certain constraints on the workflow operations, such as execution time or cost ----t~ th~ user, specified in the form of a Quality of Service (QoS) document. The users . submit their workflow to a brokering service along with the QoS document. The brokering service's task is to map any given workflow to a subset of the Grid services taking the QoS and state of the Grid into account -- service availability and performance. We propose an approach for generating constraint equations describing the workflow, the QoS requirements and the state of the Grid. This set of equations may be solved using Mixed-Integer Linear Programming (MILP), which is the traditional method. We further develop a novel 2-stage stochastic MILP which is capable of dealing with the volatile nature of the Grid and adapting the selection of the services during the lifetime of the workflow. We present experimental results comparing our approaches, showing that the . 2-stage stochastic programming approach performs consistently better than other traditional approaches. Next we addresses workload allocation techniques for Grid workflows in a multi-cluster Grid We model individual clusters as MIMIk. queues and obtain a numerical solutio~ for missed deadlines (failures) of tasks of Grid workflows. We also present an efficient algorithm for obtaining workload allocations of clusters. Next we model individual cluster resources as G/G/l queues and solve an optimisation problem that minimises QoS requirement violation, provides QoS guarantee and outperforms reservation based scheduling algorithms. Both approaches are evaluated through an experimental simulation and the results confirm that the proposed workload allocation strategies combined with traditional scheduling algorithms performs considerably better in terms of satisfying QoS requirements of Grid workflows than scheduling algorithms that don't employ such workload allocation techniques. Next we develop a novel method for Grid brokers that aims at maximising profit whilst satisfying end-user needs with a sufficient guarantee in a volatile utility Grid. We develop a develop a 2-stage stochastic MILP which is capable of dealing with the volatile nature . of the Grid and obtaining cost bounds that ensure that end-user cost is minimised or satisfied and broker's profit is maximised with sufficient guarantee. These bounds help brokers know beforehand whether the budget limits of end-users can be satisfied and. if not then???????? obtain appropriate future leases from service providers. Experimental results confirm the efficacy of our approach.Imperial Users onl

Simulation and Optimization of Production Control for Lean Manufacturing Transition

Lean manufacturing is an operations management philosophy that advocates eliminating waste, including work-in-process (WIP) inventory. A common mechanism for controlling WIP is "pull" production control, which limits the amount of WIP at each stage. The process of transforming a system from push production control to pull is not well understood or studied. This dissertation explores the events of a production control transition, quantifies its costs and develops techniques to minimize them. Simulation models of systems undergoing transition from push to pull are used to study this transient behavior. The transition of a single stage system is modeled. An objective function is introduced that defines transition cost in terms of the holding cost of orders in backlog and material in inventory. It incorporates two techniques for mitigating cost: temporarily deferring orders and adding extra capacity. It is shown that, except when backlog costs are high, it is better to transform the system quickly. It is also demonstrated that simulation based optimization is a viable tool to find the optimal transition strategy. Transition of a two-stage system is also modeled. The performance of two simple multi-stage transition strategies is measured. In the first, all of the stages are transformed at the same time. In the second, they are transformed one at a time. It is shown that the latter strategy is superior. Other strategies are also discussed. A new modeling formalism, the Production Control Framework (PCF), is introduced to facilitate automated searches for transition strategies in more complex systems. It is a hierarchical description of a manufacturing system built on a novel extension of the classic queue server model, which can express production control policy parametrically. The PCF is implemented in the form of a software template and its utility is shown as it is used to model and then find the optimal production control policy for a five stage system. This work provides the first practical guidance and insight into the behavior and cost of Lean production control transition, and it lays the groundwork for the development of optimal transition strategies for even the most complex manufacturing systems