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Constructing School Timetables using Simulated Annealing: Sequential and Parallel Algorithms
, 1991
"... : This paper considers a solution to the school timetabling problem. The timetabling problem involves scheduling a number of tuples, each consisting of class of students, a teacher, a subject and a room, to a fixed number of time slots. A Monte Carlo scheme called simulated annealing is used as an o ..."
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Cited by 70 (4 self)
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: This paper considers a solution to the school timetabling problem. The timetabling problem involves scheduling a number of tuples, each consisting of class of students, a teacher, a subject and a room, to a fixed number of time slots. A Monte Carlo scheme called simulated annealing is used as an optimisation technique. The paper introduces the timetabling problem, and then describes the simulated annealing method. Annealing is then applied to the timetabling problem. A prototype timetabling environment is described followed by some experimental results. A parallel algorithm which can be implemented on a multiprocessor is presented. This algorithm can provide a faster solution than the equivalent sequential algorithm. Some further experimental results are given. 1 INTRODUCTION This paper considers a solution to the school timetabling problem. The timetabling problem involves scheduling a number of tuples, each consisting of class of students, a teacher, a subject and a room, to a fixe...
The Solution of Real Instances of the Timetabling Problem
 The Computer Journal
, 1993
"... This paper describes a computer program for high school timetabling which has completely solved an instance taken without simplification from a large and tightly constrained high school. A timetable specification language allows the program to handle the many idiosyncratic constraints of such instan ..."
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Cited by 17 (10 self)
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This paper describes a computer program for high school timetabling which has completely solved an instance taken without simplification from a large and tightly constrained high school. A timetable specification language allows the program to handle the many idiosyncratic constraints of such instances in a uniform way. New algorithms are introduced which attack the problem more intelligently than traditional search methods. 10 August, The Solution of Real Instances of the Timetabling Problem Tim B. Cooper and Jeffrey H. Kingston Basser Department of Computer Science The University of Sydney 2006 Australia 1. Introduction The basic timetabling problem is to assign times, teachers, students, and rooms to a collection of classes and other meetings in such a way that none of the participants is required to attend two meetings simultaneously. Real instances can be very large, with hundreds of participants and hundreds of meetings squeezed into a week of about forty meeting times; and ...
The Course Scheduling Problem at Lufthansa Technical Training
, 1998
"... Lufthansa Technical Training GmbH (LTT) performs training courses for Lufthansa Technik AG as well as for several other international airlines. Courses of about 670 different types are offered of which several hundred take place each year. The course scheduling problem faced by LTT is to develop ..."
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Cited by 12 (10 self)
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Lufthansa Technical Training GmbH (LTT) performs training courses for Lufthansa Technik AG as well as for several other international airlines. Courses of about 670 different types are offered of which several hundred take place each year. The course scheduling problem faced by LTT is to develop a yearly schedule which maximizes the profit margin incurred while meeting a variety of complex precedence, temporal, and resourcerelated constraints. A "good" operational schedule should also meet a number of additional subordinate objectives. We formalize the problem and describe a heuristic scheme along with several priority rules, as well as a local search method to determine wellsuited weights for weighted composite rules. The operational planning situation of 1996 served as our major test instance; additional test instances were constructed by modifying this data. Several computational experiments were carried out to evaluate the performance of the algorithms.
Course Planning at Lufthansa Technical Training: Constructing More . . .
, 1999
"... Lufthansa Technical Training GmbH (LTT) runs training courses for Lufthansa Technik AG and for several other international airlines. It offers about 670 types of courses of which several hundred take place each year. The coursescheduling problem LTT faces is to develop a schedule for the year tha ..."
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Cited by 6 (6 self)
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Lufthansa Technical Training GmbH (LTT) runs training courses for Lufthansa Technik AG and for several other international airlines. It offers about 670 types of courses of which several hundred take place each year. The coursescheduling problem LTT faces is to develop a schedule for the year that maximizes its profit while meeting complex precedence, temporal, and resourcerelated constraints. A good operational schedule should also meet a number of subordinate objectives. In the past, LTT did all its scheduling manually. We developed a prototype coursescheduling module, using the operational planning situation of1nd as our major test instance. It turned out that most of the schedules generated were substantially better than the solution LTT constructed manually, both in terms of profit and computation time. We subsequently developed a fully fledged decisionsupport system
Solving a Time Tabling Problem by Constraint Satisfaction
, 1995
"... The time tabling problem is well known and much research has been done about it. This paper shows how a difficult instance of the time tabling problem with many parameters and loose constraints can be handled using constraint satisfaction. To this end the constraints have to be modeled in a format t ..."
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Cited by 4 (0 self)
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The time tabling problem is well known and much research has been done about it. This paper shows how a difficult instance of the time tabling problem with many parameters and loose constraints can be handled using constraint satisfaction. To this end the constraints have to be modeled in a format that can be handled efficiently. It is shown how several modelling problems can be solved in a generic way and that the results are satisfactory. 1 Introduction This paper is one in a series of papers in which we investigate the potentials of constraint satisfaction techniques to handle deterministic scheduling problems. Our research is focussed on two main lines of investigation. The first line concentrates on theoretical studies in the area of jobshop scheduling. See e.g.[6]. The second line of research investigates whether the improved performance characteristics of our constraint satisfaction algorithms also hold for problems in practical planning and scheduling situations. To this end ...
Solving Class Timetabling Problem of IIT Kanpur using MultiObjective Evolutionary Algorithm
"... Unlike in many other universities, preparation of class timetable in IIT Kanpur is very laborious and complicated. It contains different types of classes, among which most of the common classes are either split or grouped. Many split classes are divided up to five parts, while many sets of group cla ..."
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Cited by 2 (0 self)
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Unlike in many other universities, preparation of class timetable in IIT Kanpur is very laborious and complicated. It contains different types of classes, among which most of the common classes are either split or grouped. Many split classes are divided up to five parts, while many sets of group classes contain up to twenty classes. The entire timetable is composed of two phases. The first phase contains all the common compulsory classes of the institute, which are scheduled by a central team. The second phase contains the individual departmental classes. Presently this timetable is prepared manually, by manipulating those of earlier years, with the only aim of producing a feasible timetable. The potentiality of evolutionary algorithms (EAs) have been exploited in the present work to schedule the classes of the first phase of the problem. Using NSGAIIUCTO, a multiobjective EAbased university class timetable optimizer, a number of tradeoff solutions, in terms of multiple objectives of the problem, could be obtained very easily. Moreover, each of the obtained solutions has been found much better than a manually prepared solution which is in use.
Solving Timetables using Simulated Annealing Page 1 Constructing School Timetables using Simulated Annealing: Sequential and Parallel Algorithms
"... This paper considers a solution to the school timetabling problem. The timetabling problem involves scheduling a number of tuples, each consisting of class of students, a teacher, a subject and a room, to a fixed number of time slots. A Monte Carlo scheme called simulated annealing is used as an opt ..."
Abstract
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This paper considers a solution to the school timetabling problem. The timetabling problem involves scheduling a number of tuples, each consisting of class of students, a teacher, a subject and a room, to a fixed number of time slots. A Monte Carlo scheme called simulated annealing is used as an optimisation technique. The paper introduces the timetabling problem, and then describes the simulated annealing method. Annealing is then applied to the timetabling problem. A prototype timetabling environment is described followed by some experimental results. A parallel algorithm which can be implemented on a multiprocessor is presented. This algorithm can provide a faster solution than the equivalent sequential algorithm. Some further experimental results are given. 1
Professional Course Scheduling in Airline Transport Pilot Training  A Case from Lufthansa Flight Training
, 2001
"... Several wellknown and wellresearched problem fields, such as school scheduling or university scheduling, reside in the realm of educational scheduling. Recently, some new course scheduling problems have begun to draw attention, which turn out to sport substantially more complex requirements and ..."
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Several wellknown and wellresearched problem fields, such as school scheduling or university scheduling, reside in the realm of educational scheduling. Recently, some new course scheduling problems have begun to draw attention, which turn out to sport substantially more complex requirements and objectives than the classical course scheduling problems. We refer to their problem field as professional course scheduling. In order to demonstrate its practical relevance, we describe a realworld application. Lufthansa Flight Training GmbH (LFT) offers license, recurrency, emergency, and human factors training for airline, navy, and air force pilots as well as service and emergency training for cabin attendants of more than 50 airlines worldwide. This charges LFT with the problem to develop a monthly schedule for courses, instructors, and rooms that optimizes an objective function measuring adherence to seven different soft constraints while meeting a number of complex precedence, temporal, and resourcerelated constraints. In the past, LFT did all its scheduling manually, but management was dissatisfied with this process due to the significant cost and time involved. LFT commissioned us to carry out a feasibility study in which the applicability of operations research methods was to be demonstrated. We developed a prototype decision support system which utilizes construction and neighborhood search methods based upon concepts from project scheduling and graph theory. It turned out that significant improvements over the manual process could be realized; in addition, the algorithmic ideas employed are general enough to be easily adapted to other problems in the field of professional course scheduling. The development of a fullfledged decision support syst...