ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Knowledge-Based Approaches for Scheduling Problems: A Survey

Noronha, SJ and Sarma, VVS (1991) Knowledge-Based Approaches for Scheduling Problems: A Survey. In: IEEE Transactions on Knowledge and Data Engineering, 3 (2). pp. 160-171.

[img]
Preview
PDF
knowledge.pdf

Download (1541Kb)

Abstract

Scheduling is the process of devising or designing a procedure for a particular objective, specifying the sequence or time for each item in the procedure. Typical scheduling problems are railway time-tabling, project scheduling, production scheduling, and scheduling computer systems as in flexible manufacturing systems and multiprocessor scheduling. Further, there are a number of related problems belonging to the larger class of planning problems, such as the early stage of project management and resource allocation in a job shop. Scheduling is a rich area demanding the application of efficient methods to tackle the combinatorial explosion that results in real world applications. Recent developments in artificial intelligence (AI) have led to the use of knowledge-based techniques for solving scheduling problems. In this paper, we survey several existing intelligent planning and scheduling systems with the aim of providing a guide to the main AI techniques used. In view of the prevailing difference in usage of the terms planning and scheduling between AI and OR, we present a taxonomy of planning and scheduling problems. We illustrate the modeling of real world problems from closed deterministic worlds to complex real worlds with the project scheduling example. We survey some of the more successful planning and scheduling systems, and highlight their features. Finally, we consolidate the AI approaches to knowledge representation and problem solving in the project management context.

Item Type: Journal Article
Additional Information: ©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Intelligent systems;Knowledge-based systems;Planning;Project management;Scheduling
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 10 Nov 2005
Last Modified: 19 Sep 2010 04:21
URI: http://eprints.iisc.ernet.in/id/eprint/3953

Actions (login required)

View Item View Item