Organizational time: a dialectical view

We present twelve propositions constituting a contribution to a contingency view of time in organizations and synthesize apparently opposite perspectives of time. To articulate them, we relate the planning, action and improvisation strategic orientations to the dependent, independent and interdependent perspectives of the environment. Then, we relate these strategic orientations related to approaches to the problems of scheduling, synchronization and time allocation. Action strategies rely on event time to handle scheduling, use entrainment to synchronize with their environment and view time as linear. Planning strategies use even time to handle scheduling, impose their internal pacing upon the environment and view time as cyclic. Improvisation strategies use even-event time to handle scheduling, synchronize via internal-external pacing and hold a spiral view of time. Our argument strengthens the case for a more deliberate approach to time in organizations and favors a dialectical view of organizational phenomena.action, contingency, dialectics, improvisation, planning, synthesis, time

Stability and resource allocation in project planning.

The majority of resource-constrained project scheduling efforts assumes perfect information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule is executed. In reality, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. In this paper, we present a resource allocation model that protects a given baseline schedule against activity duration variability. A branch-and-bound algorithm is developed that solves the proposed resource allocation problem. We report on computational results obtained on a set of benchmark problems.Constraint satisfaction; Information; Model; Planning; Problems; Project management; Project planning; Project scheduling; Resource allocati; Scheduling; Stability; Uncertainty; Variability;

The APT/ERE planning and scheduling manifesto

The Entropy Reduction Engine, ERE project, is focusing on the construction of integrated planning and scheduling systems. Specifically, the project is studying the problem of integrating planning and scheduling in the context of the closed loop plan use. The results of this research are particularly relevant when there is some element of dynamism in the environment, and thus some chance that a previously formed plan will fail. After a preliminary study of the APT management and control problem, it was felt that it presents an excellent opportunity to show some of the ERE Project's technical results. Of course, the alignment between technology and problem is not perfect, so planning and scheduling for APTs presents some new and difficult challenges as well

A hyper-heuristic for adaptive scheduling in computational grids

In this paper we present the design and implementation of an hyper-heuristic for efficiently scheduling independent jobs in computational grids. An efficient scheduling of jobs to grid resources depends on many parameters, among others, the characteristics of the resources and jobs (such as computing capacity, consistency of computing, workload, etc.). Moreover, these characteristics change over time due to the dynamic nature of grid environment, therefore the planning of jobs to resources should be adaptively done. Existing ad hoc scheduling methods (batch and immediate mode) have shown their efficacy for certain types of resource and job characteristics. However, as stand alone methods, they are not able to produce the best planning of jobs to resources for different types of Grid resources and job characteristics. In this work we have designed and implemented a hyper-heuristic that uses a set of ad hoc (immediate and batch mode) scheduling methods to provide the scheduling of jobs to Grid resources according to the Grid and job characteristics. The hyper-heuristic is a high level algorithm, which examines the state and characteristics of the Grid system (jobs and resources), and selects and applies the ad hoc method that yields the best planning of jobs. The resulting hyper-heuristic based scheduler can be thus used to develop network-aware applications that need efficient planning of jobs to resources. The hyper-heuristic has been tested and evaluated in a dynamic setting through a prototype of a Grid simulator. The experimental evaluation showed the usefulness of the hyper-heuristic for planning of jobs to resources as compared to planning without knowledge of the resource and job characteristics.Peer ReviewedPostprint (author's final draft

Planning and Scheduling Transportation Vehicle Fleet in a Congested Traffic Environment

Transportation is a main component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routing is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic nature of travel times in this problem. In this paper, a vehicle routing problem with time windows and stochastic travel times due to potential traffic congestion is considered. The approach developed introduces mainly the traffic congestion component based on queueing theory. This is an innovative modeling scheme to capture the stochastic behavior of travel times. A case study is used both to illustrate the appropriateness of the approach as well as to show that time-independent solutions are often unrealistic within a congested traffic environment which is often the case on the european road networkstransportation; vehicle fleet; planning; scheduling; congested traffic

Protocols for distributive scheduling

The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of space shuttle mission planning

Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support

The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning

Reactive scheduling using a multi-agent model: the SCEP framework

Multi-agent systems have been successfully applied to the scheduling problem for some time. However, their use often leads to poorly unsatisfactory disappointing results. A new multi-agent model, called supervisor, customers, environment, producers (SCEP), is suggested in this paper. This model, developed for all types of planning activities, introduces a dialogue between two communities of agents leading to a high level of co-operation. Its two main interests are the following: first it provides a more efficient control of the consequences generated by the local decisions than usual systems to each agent, then the adopted architecture and behaviour permit an easy co-operation between the different SCEP models, which can represent different production functions such as manufacturing, supply management, maintenance or different workshops. As a consequence, the SCEP model can be adapted to a great variety of scheduling/planning problems. This model is applied to the basic scheduling problem of flexible manufacturing systems, andit permits a natural co-habitation between infinite capacity scheduling processes, performedby the manufacturing orders, and finite capacity scheduling processes, performed by the machines. It also provides a framework in order to react to the disturbances occurring at different levels of the workshop

An expert system for a local planning environment

In this paper, we discuss the design of an Expert System (ES) that supports decision making in a Local Planning System (LPS) environment. The LPS provides the link between a high level factory planning system (rough cut capacity planning and material coordination) and the actual execution of jobs on the shopfloor, by specifying a detailed workplan. It is divided in two hierarchical layers: planning and scheduling. At each level, a set of different algorithms and heuristics is available to anticipate different situations.\ud \ud The Expert System (which is a part of the LPS) supports decision making at each of the two LPS layers by evaluating the planning and scheduling conditions and, based on this evaluation, advising the use of a specific algorithm and evaluating the results of using the proposed algorithm.\ud \ud The Expert System is rule-based while knowledge (structure) and data are separated (which makes the ES more flexible in terms of fine-tuning and adding new knowledge). Knowledge is furthermore separated in algorithmic knowledge and company specific knowledge. In this paper we discuss backgrounds of the expert system in more detail. An evaluation of the Expert system is also presented

UIS-SCHEDULER An Asynchronous Web Enabled Collaborative Course Scheduling Tool

Course scheduling is often a labor intensive, manual process that is governed by heuristics. UIS-SCHEDULER, a WEB enabled collaborative planning tool under development at the University of Illinois, can be used to perform asynchronous planning and course scheduling. The asynchronous environment and optimization methodology for UIS-SCHEDULER aredescribed. This new scheduling tool is expected to save time and compress the planning cycle as a result of the reduction in the number of face-to-face meetings required during the planning process. Higher individual and group productivity and satisfaction with the scheduling process and outcomes are also expected as a result of the use of asynchronous technology