Decision Support System For Scheduling Research Articles

Allocation of surgical procedures to operating rooms.

Reduction of health care costs is of paramount importance in our time. This paper is a part of the research which proposes an expert hospital decision support system for resource scheduling. The proposed system combines mathematical programming, knowledge base, and database technologies, and what is more, its friendly interface is suitable for any novice user. Operating rooms in hospitals represent big investments and must be utilized efficiently. In this paper, first a mathematical model similar to job shop scheduling models is developed. The model loads surgical cases to operating rooms by maximizing room utilization and minimizing overtime in a multiple operating room setting. Then a prototype expert system which replaces the expertise of the operations research analyst for the model, drives the modelbase, database, and manages the user dialog is developed. Finally, an overview of the sequencing procedures for operations within an operating room is also presented.

Decision Support System for Scheduling

In this paper, a decision support system for operation scheduling with the name Integrated Scheduling System (ISS) is presented. The ISS is a tandem system which consists of two main subsystems: RAPO and ESPRA The RAPO subsystem is responsible for schedule generation and is based on the deterministic discrete-event simulation. A newly developed algorithm which speeded up schedule preparation has been built into RAPO. The ESPRA subsystem is an expert system that selects the most promising scheduling strategies for further use in RAPO. The inference engine of ESPRA is based on a method which optimises the solution process for any rule-based backward-chaining diagnostic system

An experiment in scheduling and planning of non-structured jobs: Lessons learned from artificial intelligence and operational research toolbox

Most scheduling problems traditionally address well defined and structured environments. Some examples include manufacturing (job shop, flow shop, etc.) and project scheduling respectively. Another type of scheduling problem that has received little or no attention is defined here as a non-structured scheduling problem (NSSP). A typical NSSP addressed here involves scheduling aircraft turnaround functions. The scheduling method consists of artificial intelligence (AI) and operational research (OR) techniques. The results obtained from the hybrid model indicate that flexibility and knowledge replication can be achieved at various levels of abstraction by converting non-structured problems to their structured equivalents. The model is implemented with TOP (a Task Oriented Planner), a decision support system for multiagent task scheduling and planning.

An FMS scheduling and control decision support system based on generalised stochastic Petri nets

This paper presents an FMS scheduling and control DSS (decision support system) using generalised stochastic Petri nets (GSPNs) for model representation and analysis. The function of the DSS is to assist the FMS operator to search for suitable control strategies that will achieve efficient performance. It can also be called upon in the event of unforeseen changes in production requirements, component failures, or other related contingencies. The GSPN modelling approach is employed because GSPNs can characterise random processing times, machine breakdown and repair rates. The GSPN employed in the proposed DSS also incorporates dispatching control at conflicting immediate transitions and can be used to determine various performance measures pertaining to scheduling and control. An application example of the DSS for the processing of two part types in a three-machine FMS is also described.

DSS for multiobjective project scheduling

The paper presents a decision support system (DSS) for multiobjective project scheduling under multiple-category resource constraints. It handles quite a general class of nonpreemptive scheduling problems with renewable, nonrenewable and doubly-constrained resources, multiple performing modes of activities, precedence constraints in the form of an activity network and multiple project performance criteria of time and cost type. The DSS is based on three kinds of heuristics: parallel priority rules, simulated annealing and branch-and-bound. The last algorithm can even yield exact solutions when sufficient processing time is available. Some parts of the system are interactive, in particular, the search for the best compromise schedule. Graphical facilities enable a thorough evaluation of feasible schedules. Methodological foundations of the system and the algorithms used in the calculation phase are first explained. Then, a functional description of the system is made. The last part presents results of three test problems, in particular, an agricultural problem including 30 activities, multiple objectives and multiple-category resources.

A decision support system for personnel scheduling in a manufacturing environment

Abstract A Decision Support System (DSS) is developed to support managers in the task of scheduling labor in the area of manufacturing. The DSS is designed to generate labor requirements by worker category and work center based on master production schedules. It is a PC-based, menu-driven program that generates a capacity plan based on data supplied by the user of the system.

Engineering of a decision support system for underground coal mine planning and production scheduling

Abstract This paper reports on the development of a computer-based management information system at Datong Coal Company, the largest subsidiary of China National Coal Corporation. Particularly presented is the development methodology of a decision support system for underground coal mine planning and production scheduling, including an integration of computer graphics, database management, mathematical modelling and knowledge engineering techniques and a coupling of life cycle and prototyping software engineering processes to support systems quality assurance.

Decentral Production Scheduling of Assembly Systems with Genetic Algorithm

In todays companies the shifting of functions from central divisions to the production areas leads to new requirements in the field of production planning. Flexible planning systems using algorithms which are adapted to the needs and the objectives of the different production areas are neccessary to fulfill these new demands. Therefore a graphical-oriented decision support system for the decentral production scheduling of assembly systems is presented. The scheduling algorithm of this system is a genetic algorithm.

A Decision Support System for Production Scheduling

ABSTRACT Production scheduling is part of the production planning, control and execution process, which covers everything from designing to manufacturing a product. From a planning point of view, scheduling is done on an operational and shop floor level. Most of the existing information systems for production planning, and control have great deficiencies in their scheduling parts. The main reasons for this are the inherent difficulties of the arising questions like combinatorial problem complexity and the difficulty in responding quickly to a dynamic and unpredictable job shop environment (machine breakdowns, rush orders, extra work etc.). Thus shop floor planning and control must be coupled with intelligent scheduling and brought close to the objects to be scheduled. For this purpose we have designed a Decision Support System which makes appropriate use of combinatorial optimization, knowledge-based and simulation techniques to help to solve the production scheduling problem.

A decision support system for operational production scheduling

In this paper we describe a Decision Support System for dynamic job shop scheduling environments. The supported decision situation includes several real-life features which are disregarded by conventional scheduling models. The system supports the planner in constructing efficient and effective schedules. The efficiency is guaranteed by algorithmic procedures and the effectiveness by interactive manipulation techniques. The due data achievement is the objective of the algorithmic support, but other objectives can be achieved by means of the control functions which allow the user to direct the decision process.

OR Practice—An Efficient Decision Support System for Academic Course Scheduling

This paper describes a network-based decision support system approach to the most general form of the academic course scheduling problem. The dimensions of faculty, subject, time, and room are considered by incorporating a penalty function into a network optimization approach. The approach, based on a network algorithm, is capable of solving very large problems. This methodology can be applied to other scheduling situations where there are competing objectives and multiple resources. Such situations include: scheduling of exams, times, and rooms in an academic setting, and scheduling of clients, times, and facilities for physicians, hospitals, dentists, counselors, and clinics. Common problems in such settings include the utilization of available space, and dissatisfaction with assigned times and locations. The proposed system results in more effective room utilization patterns, improved instructor satisfaction levels, and streamlines the tedious scheduling process. We describe the use of the model to schedule all graduate and undergraduate courses in the College of Business Administration at Texas A&M University. This involves 175 faculty, over 300 sections, 20 rooms, and 16 time slots for each semester's scheduling problem.

Multilevel Scheduling in a General Job-shop Cell

We present the framework and the algorithms of a hierarchical decision support system for scheduling in a general job-shop cell. The cell may be a part of a multi-stage production system. The scheduling model considered in the paper is compatible with the Master Planning System in which a profit-based planning objective is taken into account. The primary objective is to minimize total production costs, subject to resource and precedence constraints. The total costs include direct production costs, set-up costs, earliness and tardiness penalties and holding costs of the work-in-process.

Reflections on the architecture of a decision support system for personnel assignment scheduling in production cell technology

Within the range of new technology applications ‘flexible manufacturing systems’ are expected to give a productivity edge in market competition. Their function is based on a decentralized manufacturing organisation in form of semi-autonomous workgroups. These workgroups, consisting of a small number of workers, form so-called production cells. In this paper we want to present considerations on the architecture of a decision support system for personnel assignment scheduling within production cell organisation. Beside this, social, organisational, and qualificational aspects and requirements for the use of such systems are discussed.

Decision support system for multiproject scheduling of resources in blood collection programmes

A model of a repetitive multiproject management is introduced that includes uncertainties in activity durations, and the corresponding quantities of resources needed. Following the convention, a project is viewed here as a network of related activities aimed at the accomplishment of a predetermined objective at a given deadline. A project has a starting point in time and a preplanned completion point and so does each activity within it. The structural and operational characteristics described here are drawn from organization and management theories and used to describe project organization. This is demonstrated by means of field data gathered from a sample of ‘bloodmobile projects’ - an organized effort for the collection of blood donations in support of medical needs.

Design of a decision support system for detailed scheduling

Design of a decision support system ( DSS) based on a simulation model of the detailed scheduling activities in a tractor manufacturing company is dealt with. The system analysis phase of the design process is overviewed briefly. The main decision points involved and the problems faced in the production planning and control subsystem are presented. Expectations from a DSS for detailed scheduling are discussed and performance measures are defined. The links between computer programs are shown. Utilization of the DSS designed for production planning and control oriented decision making is discussed using decision tables.

A Visual Interactive Decision Support System For Workforce (Nurse) Scheduling

This paper describes a microcoraputer based visual interactive decision support system for workforce scheduling. A prototype system was first constructed and then tested on a nurse scheduling probl...

Microcomputer-Based Simulation Approach To Facility Overbooking

AbstractThis paper describes a microcoraputer based visual interactive decision support system for workforce scheduling. A prototype system was first constructed and then tested on a nurse scheduling problem. Following this test, significant changes were made to arrive at a final system that met the requirements of the manager of nursing services.

Design and implementation of a decision support system for academic scheduling

The task of scheduling, especially when it affects the performance of people, is a very complex endeavor. Satisfying a variety of needs and requirements while maintaining standards for efficiency and effectiveness is difficult due to political pressures exerted by those who are scheduled. The assignment of courses to professors, timeblocks, and classrooms impacts strategic planning issues such as the need for new buildings, expansion of course offerings and admission policies. This paper describes an interactive computer system made of three interrelated subsystems: the database which stores the course, professor, and classroom information; the modeling subsystem which includes all of the mathematical models used to produce the schedules, and the dialog subsystem which is designed to allow the user to change the database, execute the models to change assignments at any time, and input priorities or other subjective inputs to produce schedules. This paper also describes analysis, design, and implementation issues that arose during the creation of a Decision Support System (DSS) to aid administrators in course scheduling activities. The constraining effects of the political environment upon decision-making and DSSs are treated through the discussion of policies and their effect on DSS design. Examples from the Spring 1985 schedule of the Anderson Schools are used to expound on the issues.

Scope/Complexity: A Framework for the Classification and Analysis of Information-Decision Systems

Abstract:A new framework for the clasification and analysis of information-decision systems is presented. It is based upon two key dimensions, Scope and Complexity, each of which can be adequately described in terms of two principal components. For Scope, these are the organizational descriptors of breadth and depth, while for Complexity they are the problem descriptors of uncertainty and variety.This framework is shown to be a logical extension and synthesis of previously presented frameworks. The Scope/Complexity framework is sufficiently flexible to accommodate a variety of information system perspectives and to enable the analyst and researcher to graphically and algebraically portray the existing system and to evaluate various strategies for process improvement.An example of the application of the Scope/Complexity construct in the context of a vehicle scheduling decision support system is presented. In the final section, the Scope/Complexity framework is employed to identify a series of research hypo...

A decision support system for job shop scheduling

The paper describes an interactive job shop scheduling program and a new approach to due-date selection which is implemented in the program. The program was designed for a labour constrained workshop at the University of Stellenbosch. In scheduling models it is usually assumed that due-dates are known, either as given information or negotiated by management, before scheduling is performed. With the proposed decision support system, a job is first scheduled and then a due-date based on the scheduled lead time of the job, is calculated. The program was recently implemented and although good results were obtained, experience must still be gained in order to compare the performance of this approach to other due-date selection rules.