Ralph V. Rogers

System of Systems Engineering

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.

Job-shop scheduling: limits of the binary disjunctive formulation

SUMMARY The deterministic job-shop scheduling problem exhibits the fundamental computational difficulty implicit in determining an optimal timetable for sharing production resources among competing production activities. While adaptation of the formal model to industrial practice is fraught with difficulties, we show that the underlying binary-disjunctive formulation itself is more robust than might be immediately apparent. Straightforward extensions of the underlying model are sufficient to capture such practical problem features as assembly and disassembly sequences, due-dates and out-processing operations, scheduled maintenance, nonzero release times and dispatch operations, certain sequence-dependent set-ups and materials handling delays, and a great range of operational side-constraints. Technological sequences need not be total orders, job priorities can be assigned explicitly or implicitly, and any regular measure of performance can be represented. The principal structural limitation is that machin...

Improving computational efficiency in autonomous agent, asynchronous discrete-event simulation

Implementing independent, continuously evolving components (i.e. autonomous agents) in discrete-event simulation while providing a useful and efficient broadbased modeling methodology has proven a challenge to the simulation community. Reasons for these difficulties are innate to the implementation of current accepted simulation modeling practices and theories of clock advances, modeling world view, and network modeling paradigms. Meeting the challenge of implementing autonomous agents requires understanding the underlying factors and issues hindering further development. This paper identifies these factors and offers sectoring as basis for building an efficient methodology for autonomous agents in discrete-event simulation.<<ETX>>

What makes a modeling and simulation professional?: The consensus view from one workshop

This paper is part of a focused paper panel discussion addressing the results of an invited workshop conducted in Orlando, Florida in February, 1997. The workshop addressed the question: What makes a modeling and simulation professional? The workshops results included a consensus ideal modeling and simulation professional characterized by eight categories and subsequent elements. Each of the eight categories and elements are presented as well as contextual narrative. The author provides an interpretation of the workshop results and implications for modeling and simulation professionals. Panel members were asked to respond to the goals and results of the workshop, as well as, the authors interpretations and comments of this paper. The paper and panel discussion are an attempt to spark debate on the modeling and simulation profession.

Algebraic, mathematical programming, and network models of the deterministic job-shop scheduling problem

In the contemporary literature on deterministic machine scheduling, problems are formulated from three different, but equivalent, perspectives. Algebraic models provide a rigorous problem statement in the language of set theory and are typical of the more abstract development of scheduling theory in mathematics and computer science. Mathematical programming models rely on familiar concepts of nonlinear optimization and are generally the most accessible. Network models (disjunctive graphs) are best suited to the development of solution approaches and figure prominently in discussions of algorithm design and analysis. In this tutorial, it is shown how the minimum-makespan job-shop problem (n/m/G/C/sub max/) is realized in each of these three model forms. A common notation is developed and how the underlying structure and fundamental difficulty of the problem are expressed in each model is demonstrated. >

Conceptions of curriculum for simulation education

In the Winter Simulation Conference 1999 in Phoenix, a series of discussions, conversations, and exchanges on the topic of personnel to meet the current modeling and simulation demands of the civilian application and world military as well led to the idea of giving this discussion a more structured shape in the Winter Simulation Conference 2000. We continue to discuss the complex issue of Simulation Education. A general demand for modeling and simulation professionals can be observed in a large number of enterprises. However computer science graduates are not adequately prepared for employment opportunities involving simulation as a tool in solving problems. Most computer science majors have very limited exposure to simulation. They gain experience in handling of simulation problems by on-the-job-training. Moreover, there doesn’t exist any consensus of simulation as a discipline. The following questions hence emerge:

The development of knowledge for maintenance management using simulation

The management of maintenance is an area of concern for any industry that depends on the smooth running of equipment to produce a product or carry out a mission at profit or low cost. Maintenance managers must have access to advanced information systems to help them plan their work forces and control operating costs efficiently. This paper describes a method and demonstrates its use to develop a knowledge base for a maintenance supervisor assistant system (MSAS). MSAS interacts with the maintenance manager on a periodic basis to select, for the next period of operations, the proper policies and techniques to meet objectives. The first stage of the method is the knowledge acquisition phase. For this phase, an object-oriented computer simulation model has been developed as a testbed for examining different scheduling heuristics and manning policies in a range of maintenance environments. The dimensions of the environment considered include: preventive maintenance policies, staffing policies, downtime costs, simultaneous downtime practices, travel time impacts, and backlog policies. The dependent variables of interest include: overall machine availability, critical machine availability, worker utilization, cost of the maintenance function, and work order completion time. The second stage is a knowledge engineering effort to codify what is learned from the stage one simulation experiments into a knowledge base for a MSAS. A procedure for deriving expert system rules from simulation experiments is demonstrated. This is followed by validation of the knowledge base through re-employment of the simulation model. >

Autonomy: simulation's next events

Simulation is facing the challenge to support ever increasingly complex phenomena characterized by autonomous behavior. This paper discusses an approach with which to investigate the wider modeling and analysis issues raised by these demand.

Achieving O(N) in simulating the billiards problem in discrete-event simulation

The paper identifies underlying issues associate with simulating those classes of problems which require both arbitrary spatial and temporal precision and which must deal the with the complexities of a multitude of asynchronous pair-wise interactions occuring among a dynamic non-uniform distribution of numerous spatial components. The principal issue of interest discussed focuses on a proposed simulation modeling methodology which dynamically sectors the trajectory space based on the number of spatial objects occupying a portion of the trajectory space (i.e. object space density). That is, the trajectory space is divided into sectors of various sizes such that each sector contains no more than some specified number of spatial components. The authors demonstrate that with such a dynamic sectoring methodology a theoretical reduction in the total number of pair-wise comparisons required during each time advancement can be achieved. Additionally, the theoretical computational complexity associated with identifying spatial conflicts will be better than O(N/sup 2/) for a non-uniform distribution of N spatial objects.

The Simulation Professional Certification Program: a status report

Under the auspices of the National Training Systems Association, a program was developed to establish organizations and processes whereby professional certification for the modeling and simulation industry may be conducted in a consistent and dependable way. The Modeling and Simulation Professional Certification Commission (MSPCC) was envisioned with the mission to develop and provide the professional certification. The Implementation Group was formed to define and implement the MSPCC and establish the Modeling and Simulation Professional Certification Board (MSPCB), an element of the Commission. This paper provides a status report on the efforts of the Commission and the Board to establish and certification program for modeling and simulation professionals.