Multiple-retrieval case-based reasoning for course timetabling problems

The structured representation of cases by attribute graphs in a case-based reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organized as a decision tree and the retrieval process chooses those cases that are sub-attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependent upon problem-specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialization method for local search methods such as hill climbing, tabu search and simulated annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialization method for these approaches.     

RobinX: A three-field classification and unified data format for round-robin sports timetabling

Sports timetabling problems are combinatorial optimization problems which consist of creating a timetable that defines against whom, when, and where teams play games. In the literature, sports timetabling problems have been reported featuring a wide variety of constraints and objectives. This variety makes it challenging to identify the relevant set of papers for a given sports timetabling problem. Moreover, the lack of a generally accepted data format makes that problem instances and their solutions are rarely shared. Consequently, it is hard to assess algorithmic performance since solution methods are often tested on just one or two specific instances. To mitigate these issues, this paper presents RobinX, a three-field notation to describe a sports timetabling problem by means of the tournament format, the constraints in use, and the objective. We use this notation to classify sports timetabling problems presented in the operations research literature during the last five decades. Moreover, RobinX contains xml-based file templates to store problem instances and their solutions and presents an online platform that offers three useful tools. First, a query tool assists users to select the relevant set of papers for a given timetabling problem. Second, the online platform provides access to an xml data repository that contains real-life problem instances from different countries and sports. Finally, the website enables users to interact with a free and open-source C++-library to read and write xml files and to validate and evaluate encoded instances and solutions.     

A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem

Neighbourhood search algorithms are often the most effective known approaches for solving partitioning problems. In this paper, we consider the capacitated examination timetabling problem as a partitioning problem and present an examination timetabling methodology that is based upon the large neighbourhood search algorithm that was originally developed by Ahuja and Orlin. It is based on searching a very large neighbourhood of solutions using graph theoretical algorithms implemented on a so-called improvement graph. In this paper, we present a tabu-based large neighbourhood search, in which the improvement moves are kept in a tabu list for a certain number of iterations. We have drawn upon Ahuja–Orlin's methodology incorporated with tabu lists and have developed an effective examination timetabling solution scheme which we evaluated on capacitated problem benchmark data sets from the literature. The capacitated problem includes the consideration of room capacities and, as such, represents an issue that is of particular importance in real-world situations. We compare our approach against other methodologies that have appeared in the literature over recent years. Our computational experiments indicate that the approach we describe produces the best known results on a number of these benchmark problems.     

Efficient solutions for a university timetabling problem through integer programming

Integer programming has always been an alternative for formulating combinatorial problems such as the university timetabling problem. However, the effort required for modeling complicated operational rules, as well as the computational difficulties that result from the size of real problems have discouraged researchers and made them turn their interest to other approaches. In this paper, a two-stage relaxation procedure that solves efficiently the integer programming formulation of a university timetabling problem is presented. The relaxation is performed in the first stage and concerns the constraints that warrantee consecutiveness in multi-period sessions of certain courses. These constraints, which are computationally heavier than the others, are recovered during the second stage and a number of sub-problems, one for each day of the week, are solved for local optima. Comparing to a solution approach that solves the problem in a single stage, computation time is reduced significantly without any loss in quality for the resulting timetables. The new solution approach gives a chance for further improvements in the final timetables, as well as for certain degree of interaction with the users during the construction of the timetables.     

A stochastic local search algorithm with adaptive acceptance for high-school timetabling

Automating high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers. High schools need to timetable their regular activities once per year, or even more frequently. The exact solvers might fail to find a solution for a given instance of the problem. A selection hyper-heuristic can be defined as an easy-to-implement, easy-to-maintain and effective ‘heuristic to choose heuristics’ to solve such computationally hard problems. This paper describes the approach of the team hyper-heuristic search strategies and timetabling (HySST) to high school timetabling which competed in all three rounds of the third international timetabling competition. HySST generated the best new solutions for three given instances in Round 1 and gained the second place in Rounds 2 and 3. It achieved this by using a fairly standard stochastic search method but significantly enhanced by a selection hyper-heuristic with an adaptive acceptance mechanism.     

University timetabling by constraint-based reasoning: A case study

This paper presents a case-study which applies constraint-based reasoning to university timetable planning. The timetabling problem is formulated as a constraint satisfaction model and this model is solved using constrained-directed search algorithms with built-in forward checking and constraint propagation. The model and algorithms were tested with real data containing 536 lessons to be scheduled into 45 timeslots and 21 rooms. The solution to the problem was obtained with minimal computing effort and processing time. This study showed that modelling and remodelling could be carried out easily through a proposed parameterised model formulation. The proposed approach has also successfully maximised room utilisation and minimised the number of timeslots required to deliver all the lectures. This finding may facilitate the widespread implementation of automated timetabling systems to larger scale problems and a wider variety of application domains.     

Recent research directions in automated timetabling

The aim of this paper is to give a brief introduction to some recent approaches to timetabling problems that have been developed or are under development in the Automated Scheduling, Optimisation and Planning Research Group (ASAP) at the University of Nottingham. We have concentrated upon university timetabling but we believe that some of the methodologies that are described can be used for different timetabling problems such as employee timetabling, timetabling of sports fixtures, etc. The paper suggests a number of approaches and comprises three parts. Firstly, recent heuristic and evolutionary timetabling algorithms are discussed. In particular, two evolutionary algorithm developments are described: a method for decomposing large real-world timetabling problems and a method for heuristic initialisation of the population. Secondly, an approach that considers timetabling problems as multicriteria decision problems is presented. Thirdly, we discuss a case-based reasoning approach that employs previous experience to solve new timetabling problems. Finally, we outline some new research ideas and directions in the field of timetabling. The overall aim of these research directions is to explore approaches that can operate at a higher level of generality than is currently possible.     

A Tabu-Search Hyperheuristic for Timetabling and Rostering

Hyperheuristics can be defined to be heuristics which choose between heuristics in order to solve a given optimisation problem. The main motivation behind the development of such approaches is the goal of developing automated scheduling methods which are not restricted to one problem. In this paper we report the investigation of a hyperheuristic approach and evaluate it on various instances of two distinct timetabling and rostering problems. In the framework of our hyperheuristic approach, heuristics compete using rules based on the principles of reinforcement learning. A tabu list of heuristics is also maintained which prevents certain heuristics from being chosen at certain times during the search. We demonstrate that this tabu-search hyperheuristic is an easily re-usable method which can produce solutions of at least acceptable quality across a variety of problems and instances. In effect the proposed method is capable of producing solutions that are competitive with those obtained using state-of-the-art problem-specific techniques for the problems studied here, but is fundamentally more general than those techniques.     

Timetabling for Greek high schools

The timetabling process and the resulting weekly schedules are important components for the daily operation of any school. This paper presents an efficient solution to the timetabling problem for the secondary educational system in Greece. Such a problem involves scheduling a large number of classes, teachers, courses, and classrooms to a number of time-periods. The development of the basic structure and the modelling of the problem as an integer mathematical program allows for the generation of constraints necessary for the satisfaction of all the school system rules and regulations. The integer programming approach and the commercial tools available for this class of problems facilitated the process of locating the optimal solution for the problem. The model is flexible and modular allowing for adaptations to satisfy the local characteristics of each school by changing the parameters of the model and adding or replacing constraints. A fully defined timetabling problem for a typical Greek high school is presented and optimally solved in order to demonstrate the effectiveness of the model in satisfying both the hard and the soft operational rules of the problem. Implementation of the new methodology for regular use for high schools is currently being attempted.     

Pattern-based models and a cooperative parallel metaheuristic for high school timetabling problems

High school timetabling problems consist in building periodic timetables for class-teacher meetings considering compulsory and non-compulsory requirements. This family of problems has been widely studied since the 1950s, mostly via mixed-integer programming and metaheuristic techniques. However, the efficient search of optimal or near-optimal solutions is still a challenge for many problems of practical size. In this paper, we investigate mixed-integer programming formulations and a parallel metaheuristic based algorithm for solving high school timetabling problems with compactness and balancing requirements. We propose two pattern-based formulations and a solution algorithm that simultaneously exploits column generation and a team of metaheuristics to build and improve solutions. Extensive computational experiments conducted with real-world instances demonstrate that our formulations are competitive with the best existing high school timetabling formulations, while our parallel algorithm presents superior performance to alternative methods available in the literature.     

An improved multi-staged algorithmic process for the solution of the examination timetabling problem

The efficient creation of examination timetables is a recurring and important problem for universities worldwide. Good timetables typically are characterized by balanced distances between consecutive exams for all students. In this contribution an approach for the examination timetabling problem as defined in the second International Timetabling Competition () is presented. The solution approach is managed on the top level by GRASP (Greedy Randomized Adaptive Search Procedure) and it involves several optimization algorithms, heuristics and metaheuristics. A construction phase is executed first producing a relatively high quality feasible solution and an improvement phase follows that further ameliorates the produced timetable. Each phase consists of stages that are consumed in a circular fashion. The procedure produces feasible solutions for each dataset provided under the runtime limit imposed by the rules of the ITC07 competition. Results are presented and analyzed.     

Theory of convex cones in multicriteria decision making

We develop the theory of convex polyhedral cones in the objective-function space of a multicriteria decision problem. The convex cones are obtained from the decision-maker's pairwise judgments of decision alternatives and are applicable to any quasiconcave utility function. Therefore, the cones can be used in any progressively articulated solution procedure that employs pairwise comparisons. The cones represent convex sets of solutions that are inferior to known solutions to a multicriteria problem. Therefore, these convex sets can be eliminated from consideration while solving the problem. We develop the underlying theory and a framework for representing knowledge about the decision-maker's preference structure using convex cones. This framework can be adopted in the interactive solution of any multicriteria problem after taking into account the characteristics of the problem and the solution procedure. Our computational experience with different multicriteria problems shows that this approach is both viable and efficient in solving practical problems of moderate size.     

Complete local search with limited memory algorithm for no-wait job shops to minimize makespan

In this paper, no-wait job shop problems with makespan minimization are considered. It is well known that these problems are strongly NP-hard. The problem is decomposed into the sequencing and the timetabling components. Shift timetabling is developed for the timetabling component. An effective method, CLLM (complete local search with limited memory), is presented by integrating with shift timetabling for the sequencing component. Experimental results show that CLLM outperforms all the existing effective algorithms for the considered problem with a little more computation time.     

多变量、多约束连续或离散的非线性规划的一个通用算法

利用目标函数对约束函数关于设计变量的一阶微分或差分之比,给出了一个求解非线性规划的通用算法．不论变量和约束有多少,也不论变量是连续的还是离散的,这一算法都比较有效,尤其对离散非线性规划更有效．该方法是一种搜索法,勿需解任何数学方程,只需要计算函数值以及函数对变量的偏微分或差分值．许多数值例题和运筹学中一些经典问题,如1) 一、二维的背包问题;2) 一、二维资源分配问题;3) 复合系统工作可靠性问题;4) 机器负荷问题等,经用此法求解验证均较传统方法更有效和可靠．该方法的主要优点是:1) 不受问题的规模限制;2) 只要在可行域（集）内存在目标函数和约束函数及其一阶导数或差分的值,肯定可以搜索到最优的解,没有不收敛和不稳定的问题．     

A Global Optimization Approach to a Water Distribution Network Design Problem

In this paper, we address a global optimization approach to a waterdistribution network design problem. Traditionally, a variety of localoptimization schemes have been developed for such problems, each new methoddiscovering improved solutions for some standard test problems, with noknown lower bound to test the quality of the solutions obtained. A notableexception is a recent paper by Eiger et al. (1994) who present a firstglobal optimization approach for a loop and path-based formulation of thisproblem, using a semi-infinite linear program to derive lower bounds. Incontrast, we employ an arc-based formulation that is linear except forcertain complicating head-loss constraints and develop a first globaloptimization scheme for this model. Our lower bounds are derived through thedesign of a suitable Reformulation-Linearization Technique (RLT) thatconstructs a tight linear programming relaxation for the given problem, andthis is embedded within a branch-and-bound algorithm. Convergence to anoptimal solution is induced by coordinating this process with an appropriatepartitioning scheme. Some preliminary computational experience is providedon two versions of a particular standard test problem for the literature forwhich an even further improved solution is discovered, but one that isverified for the first time to be an optimum, without any assumed boundson the flows. Two other variants of this problem are also solved exactly forillustrative purposes and to provide researchers with additional test caseshaving known optimal solutions. Suggestions on a more elaborate study involving several algorithmic enhancements are presented for futureresearch.     

Universiti Malaysia Pahang examination timetabling problem: scheduling invigilators

This paper presents a real-world examination timetabling problem from Universiti Malaysia Pahang (UMP), Malaysia. The problem involves assigning invigilators to examination rooms. This problem has received less attention than the examination timetabling problem from the research community partly because no data sets are available in the literature. In modelling, and solving, this problem we assume that there is already an examination timetable in place (this was the subject of our previous work) and the task is to assign invigilators to that timetable. The contributions of this paper are to formally define the invigilator scheduling problem and to present a constructive algorithm that is able to produce good quality solutions that are superior to the solutions produced when using the university's current software. We also include additional constraints taking into account the comments made by the invigilators, which the current system fails to capture. The model we present, we believe, accurately reflects the real-world problem, capturing various aspects of the problem that have not been presented before in the scientific literature. Moreover, the proposed approach adheres to all hard constraints, which the university's current system fails to do.     

University course timetabling using hybridized artificial bee colony with hill climbing optimizer

University course timetabling is concerned with assigning a set of courses to a set of rooms and timeslots according to a set of constraints. This problem has been tackled using metaheuristics techniques. Artificial bee colony (ABC) algorithm has been successfully used for tackling uncapaciated examination and course timetabling problems. In this paper, a novel hybrid ABC algorithm based on the integrated technique is proposed for tackling the university course timetabling problem. First of all, initial feasible solutions are generated using the combination of saturation degree (SD) and backtracking algorithm (BA). Secondly, a hill climbing optimizer is embedded within the employed bee operator to enhance the local exploitation ability of the original ABC algorithm while tackling the problem. Hill climbing iteratively navigates the search space of each population member in order to reach a local optima. The proposed hybrid ABC technique is evaluated using the dataset established by Socha including five small, five medium and one large problem instances. Empirical results on these problem instances validate the effectiveness and efficiency of the proposed algorithm. Our work also shows that a well-designed hybrid technique is a competitive alternative for addressing the university course timetabling problem.     

A survey of school timetabling research

Although there has been a fair amount of research in the area of school timetabling, this domain has not developed as well as other fields of educational timetabling such as university course and examination timetabling. This can possibly be attributed to the fact that the studies in this domain have generally been conducted in isolation of each other and have addressed different school timetabling problems. Furthermore, there have been no comparative studies on the success of different methodologies on a variety of school timetabling problems. As a way forward this paper provides an overview of the research conducted in this domain, details of problem sets which are publicly available and proposes areas for further research in school timetabling.     

Timetabling University Examinations

The problem of timetabling examinations is one which is faced by most educational institutions, with the problem becoming particularly acute in institutions of higher education. The situation may be formulated generally as a 0-1 integer pregramming problem but, in common with a number of other timetabling problems which have been reported, a heuristic approach is more practical and produces an acceptable solution. The procedure described takes account of the obvious constraints imposed by examination-room availability and capacity, and the need to avoid clashes between common examination papers. In addition, the examinations are scheduled such that the students are faced with a minimum number of occasions when two papers have to be taken in the same day and, for ease of marking, the larger courses are examined early. A computer program to implement the heuristic was developed and was found to produce a better timetable than the previous manual procedure as well as a considerable saving in clerical effort.     

Real-life curriculum-based timetabling with elective courses and course sections

This paper presents an innovative approach to curriculum-based timetabling. To capture complex relations of real life curriculum-based timetabling problems, curricula are defined by a rich model that includes optional courses and course groups among which students are expected to take a subset of courses. In addition, courses may contain alternative course sections. A transformation between the proposed curriculum model and student course enrollments is formalized and a local search algorithm generating corresponding enrollments is introduced. While the proposed curriculum model is too complicated for existing curriculum-based solvers, the transformation enables curriculum-based timetabling in any existing enrollment-based course timetabling solver. The approach was implemented in a well established enrollment-based course timetabling system UniTime. The system has been successfully applied in practice at the Faculty of Education at Masaryk University for about 7,500 students and 260 curricula and at the Faculty of Sports Studies at Masaryk University for about 1,400 students and 25 curricula. Experimental results related with these problems are demonstrated for two semesters.