A GRASP strategy for a more constrained School Timetabling Problem

Moura, Arnaldo Vieira; Scaraficci, Rafael Augusto

doi:10.1504/ijor.2010.030801

Cited by 30 publications

(18 citation statements)

References 21 publications

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“…Other approaches used in high school timetabling problem include adaptive Evolutionary Computation Volume x, Number x large neighbourhood search (Sørensen et al, 2012), integer programming (Birbas et al, 2009), particle swarm optimisation (Tassopoulos and Beligiannis, 2012), tiling algorithms (Kingston, 2005), bee algorithms (Lara et al, 2008), Hopfield neural networks (Smith et al, 2003), walk down jump up algorithm (Wilke and Killer, 2010), greedy randomised adaptive search procedure (Moura and Scaraficci, 2010) and constraint programming approach (Valouxis and Housos, 2003). For the recent survey on high school timetabling problem the reader is directed to (Pillay, 2013).…”

Section: High School Timetabling Problemsmentioning

confidence: 99%

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

Kheiri

Keedwell

2017

Evolutionary Computation

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Operations research is a well established field that uses computational systems to support decisions in business and public life. Good solutions to operations research problems can make a large difference to the efficient running of businesses and organisations and so the field often searches for new methods to improve these solutions. The high school timetabling problem is an example of an operations research problem and is a challenging task which requires assigning events and resources to time slots subject to a set of constraints. In this paper a new sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling problems. In this study, we present an easy-to-implement, easy-to-maintain and effective sequence-based selection hyper-heuristic to solve high school timetabling problems using a benchmark of unified real-world instances collected from different countries. We show that with sequence-based methods, it is possible to discover new best known solutions for a number of the problems in the timetabling domain. Through this investigation, the usefulness of sequence-based selection hyper-heuristics has been demonstrated and the capability of these methods has been shown to exceed the state-of-theart.

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Section: High School Timetabling Problemsmentioning

confidence: 99%

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

Kheiri

Keedwell

2017

Evolutionary Computation

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“…Raghavjee and Pillay (2010) described a hybrid evolutionary algorithm with no crossover using a hill climber for solving a South African high school course timetabling problem along with a primary school timetabling problem. Moura and Scaraficci (2010) applied the greedy randomised adaptive search procedure (GRASP) heuristic to solve a Brazilian high school timetabling problem. Pillay (2010b) implemented an evolutionary algorithm based hyper-heuristic selection method.…”

Section: High School Timetabling Problemmentioning

confidence: 99%

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

2014

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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.

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“…The objective function of the CVRP that should be minimized is the total cost distance travelled by all the vehicles. The problem is solved subject to the following constraint [24,25]:…”

Section: Capacitated Vehicle Routing Problem Formulationmentioning

confidence: 99%

“…GRASP is a two-phase metaheuristic technique used to solve hard combinatorial optimization problems. The first phase is a constructive phase used for the construction of initial solutions while the second phase is generally a local search method used for the improvement of the solutions found in the first phase [23,24]. A generic GRASP approach is described in Figure 1.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

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A GRASP Algorithm Based on New Randomized Heuristic for Vehicle Routing Problem

Layeb

Ammi

Chikhi

2013

CIT

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This paper presents a novel GRASP algorithm based on a new randomized heuristic for solving the capacitated vehicle routing problem. This problem is characterized by a fleet of homogenous vehicle capacity that will start from one depot, to serve a number of customers with demands that are less than the vehicle capacity. The proposed method is based on a new constructive heuristic, and a simulated annealing procedure as an improvement phase. The new constructive heuristic uses four steps to generate feasible initial solutions, and the simulated annealing enhances these solutions found to reach the optimal one. We tested our algorithm on two sets of benchmark instances and the obtained results are very encouraging.

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A GRASP strategy for a more constrained School Timetabling Problem

Cited by 30 publications

References 21 publications

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

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

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

A GRASP Algorithm Based on New Randomized Heuristic for Vehicle Routing Problem

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