All Outputs (12)

An Efficient Application of Goal Programming to Tackle Multiobjective Problems with Recurring Fitness Landscapes (2019)
Book Chapter

© 2019, Springer Nature Switzerland AG. Many real-world applications require decision-makers to assess the quality of solutions while considering multiple conflicting objectives. Obtaining good approximation sets for highly constrained many-objective... Read More about An Efficient Application of Goal Programming to Tackle Multiobjective Problems with Recurring Fitness Landscapes.

Non-linear great deluge with reinforcement learning for university course timetabling (2011)
Book Chapter

This paper describes a non-linear great deluge hyper-heuristic incorporating a reinforcement learning mechanism for the selection of low-level heuristics and a non-linear great deluge acceptance criterion. The proposed hyper-heuristic deals with comp... Read More about Non-linear great deluge with reinforcement learning for university course timetabling.

Computational study of non-linear great deluge for university course timetabling (2010)
Book Chapter

The great deluge algorithm explores neighbouring solutions which are accepted if they are better than the best solution so far or if the detriment in quality is no larger than the current water level. In the original great deluge method, the water le... Read More about Computational study of non-linear great deluge for university course timetabling.

Discovering beneficial cooperative structures for the automated construction of heuristics (2010)
Book Chapter

The current research trends on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to... Read More about Discovering beneficial cooperative structures for the automated construction of heuristics.

An improved version of volume dominance for multi-objective optimisation (2009)
Book Chapter

This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volume dominance on the performance of multi-objective evolutionary algorithms is inve... Read More about An improved version of volume dominance for multi-objective optimisation.

Evolutionary non-linear great deluge for university course timetabling (2009)
Book Chapter

This paper presents a hybrid evolutionary algorithm to tackle university course timetabling problems. The proposed approach is an extension of a non-linear great deluge algorithm in which evolutionary operators are incorporated. First, we generate a... Read More about Evolutionary non-linear great deluge for university course timetabling.

Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach (2009)
Book Chapter

This paper investigates the ability of a discrete particle swarm optimization algorithm (DPSO) to evolve solutions from infeasibility to feasibility for the Vehicle Routing Problem with Time Windows (VRPTW). The proposed algorithm incorporates some p... Read More about Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach.

A simple evolutionary algorithm with self-adaptation for multi-objective nurse scheduling (2008)
Book Chapter

We present a multi-objective approach to tackle a real-world nurse scheduling problem using an evolutionary algorithm. The aim is to generate a few good quality non-dominated schedules so that the decision-maker can select the most appropriate one. O... Read More about A simple evolutionary algorithm with self-adaptation for multi-objective nurse scheduling.

Adaptive and assortative mating scheme for evolutionary multi-objective algorithms (2008)
Book Chapter

We are interested in the role of restricted mating schemes in the context of evolutionary multi-objective algorithms. In this paper, we propose an adaptive assortative mating scheme that uses similarity in the decision space (genotypic assortative ma... Read More about Adaptive and assortative mating scheme for evolutionary multi-objective algorithms.

The teaching space allocation problem with splitting (2006)
Book Chapter

A standard problem within universities is that of teaching space allocation which can be thought of as the assignment of rooms and times to various teaching activities. The focus is usually on courses that are expected to fit into one room. However,... Read More about The teaching space allocation problem with splitting.

Multi-objective hyper-heuristic approaches for space allocation and timetabling (2005)
Book Chapter

An important issue in multi-objective optimisation is how to ensure that the obtained non-dominated set covers the Pareto front as widely as possible. A number of techniques (e.g. weight vectors, niching, clustering, cellular structures, etc.) have b... Read More about Multi-objective hyper-heuristic approaches for space allocation and timetabling.

Three methods to automate the space allocation process in UK universities (2001)
Book Chapter

The space allocation problem within UK universities is highly constrained, has multiple objectives, varies greatly among different institutions, requires frequent modifications and has a direct impact on the functionality of the university. As in eve... Read More about Three methods to automate the space allocation process in UK universities.