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

Abstract

Automated 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 may 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 HySST (Hyper-heuristic Search Strategies and Timetabling) to high school timetabling which competed at the three rounds of the Third International Timetabling Competition. Despite this being the first attempt in high school timetabling, HySST generated the best new solutions for three given instances in Round 1 and gained the second place in Rounds 2 and 3 with a fairly standard stochastic search method but significantly enhanced by a selection hyper-heuristic with an adaptive acceptance mechanism.

Evolutionary Hyperheuristics for Location-Routing Problem with Simultaneous Pickup and Delivery

“…With the popularity of hyperheuristic, it has been widely applied in practice, such as 2D regular and irregular packing problems [73], nurse rostering [74], vehicle routing problem [54], construction levelling problem [52], software project scheduling problem [56], t-ways test suite generation [6,75], deriving products for variability test of feature models [55], fast machine reassignment [76], and timetabling [77][78][79][80][81]. We refer interested readers to these papers [43,82,83] for extensive review on hyperheuristic.…”

A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems

“…GOAL combined iterated local search with simulated annealing (Fonseca et al, 2014). HySST applied a stochastic local search hyper-heuristic (Kheiri et al, 2016). Lectio employed an approach based on adaptive large neighbourhood search (Sørensen et al, 2012).…”

A Comparative Study of Modern Heuristics on the School Timetabling Problem

“…In the respective literature many variants of the high school timetabling problem have been presented, which mainly differ due to the educational system of each country [5][6][7]. In recent years many papers have been published describing specific techniques applied to the high school timetabling problem [8][9][10][11][12][13][14][15].…”