Book•
Scheduling: Theory, Algorithms, and Systems
15 Jul 1994-
TL;DR: Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
Abstract: This book on scheduling covers theoretical models as well as scheduling problems in the real world. Author Michael Pinedo also includes a CD that contains slide-shows from industry and movies dealing with implementations of scheduling systems. The book consists of three parts. The first part focuses on deterministic scheduling with the associated combinatorial problems. The second part covers probabilistic scheduling models. In this part it is assumed that processing times and other problem data are not known in advance. The third part deals with scheduling in practice. It covers heuristics that are popular with practitioners and discusses system design and development issues. Each chapter contains a series of computational and theoretical exercises. This book is of interest to theoreticians and practitioners alike. Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource. Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments. Michael Pinedo is the Julius Schlesinger Professor of Operations Management at New York University.
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TL;DR: This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service.
Abstract: The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online business-to-business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different quality of service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming.
2,872 citations
Cites background from "Scheduling: Theory, Algorithms, and..."
...When a task actually needs to be executed, the system collects information about the QoS of each of the Web services that can execute this task (namely the candidate Web services for this task)....
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TL;DR: It is shown that for the cases studied here, the relatively simple Min?min heuristic performs well in comparison to the other techniques, and one even basis for comparison and insights into circumstances where one technique will out-perform another.
1,757 citations
Cites background from "Scheduling: Theory, Algorithms, and..."
...The maximum ct(ti , mj) value, over 0 i<{ and 0 j<+, is the metatask execution time, and is called the makespan [32]....
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TL;DR: An extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers is provided, which classifies scheduling problems into those with batching and non-batching considerations, and with sequence-independent and sequence-dependent setup times.
1,264 citations
20 May 2003
TL;DR: This paper proposes a global planning approach to optimally select component services during the execution of a composite service, and experimental results show that thisglobal planning approach outperforms approaches in which the component services are selected individually for each task in a Composite service.
Abstract: The process-driven composition of Web services is emerging as a promising approach to integrate business applications within and across organizational boundaries. In this approach, individual Web services are federated into composite Web services whose business logic is expressed as a process model. The tasks of this process model are essentially invocations to functionalities offered by the underlying component services. Usually, several component services are able to execute a given task, although with different levels of pricing and quality. In this paper, we advocate that the selection of component services should be carried out during the execution of a composite service, rather than at design-time. In addition, this selection should consider multiple criteria (e.g., price, duration, reliability), and it should take into account global constraints and preferences set by the user (e.g., budget constraints). Accordingly, the paper proposes a global planning approach to optimally select component services during the execution of a composite service. Service selection is formulated as an optimization problem which can be solved using efficient linear programming methods. Experimental results show that this global planning approach outperforms approaches in which the component services are selected individually for each task in a composite service.
1,229 citations
01 Jan 2013
TL;DR: In today’s changing and competitive industrial environment, the difference between ad hoc planning methods and those that use sophisticated mathematical models to determine an optimal course of action can determine whether or not a company survives.
Abstract: Integer optimization problems are concerned with the efficient allocation of limited resources to meet a desired objective when some of the resources in question can only be divided into discrete parts. In such cases, the divisibility constraints on these resources, which may be people, machines, or other discrete inputs, may restrict the possible alternatives to a finite set. Nevertheless, there are usually too many alternatives to make complete enumeration a viable option for instances of realistic size. For example, an airline may need to determine crew schedules that minimize the total operating cost; an automotive manufacturer may want to determine the optimal mix of models to produce in order to maximize profit; or a flexible manufacturing facility may want to schedule production for a plant without knowing precisely what parts will be needed in future periods. In today’s changing and competitive industrial environment, the difference between ad hoc planning methods and those that use sophisticated mathematical models to determine an optimal course of action can determine whether or not a company survives.
1,066 citations
Cites background from "Scheduling: Theory, Algorithms, and..."
...The literature on scheduling problems is extremely rich and many variants of the basic problem have been suggested (Pinedo, 2008)....
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...Jünger et al. (2010) have produced a marvelous and comprehensive volume containing an overview of both the history and current state of the art in integer and combinatorial optimization....
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