All Outputs (24)

Local-global methods for generalised solar irradiance forecasting (2024)
Journal Article

For efficient operation, solar power operators often require generation forecasts for multiple sites with varying data availability. Many proposed methods for forecasting solar irradiance / solar power production formulate the problem as a time-serie... Read More about Local-global methods for generalised solar irradiance forecasting.

EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification (2020)
Journal Article

© 2020 Learning from imbalanced datasets is highly demanded in real-world applications and a challenge for standard classifiers that tend to be biased towards the classes with the majority of the examples. Undersampling approaches reduce the size of... Read More about EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification.

Adaptive multiple crossover genetic algorithm to solve workforce scheduling and routing problem (2018)
Journal Article

The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits, across various geographical locations. Solving this problem demands tackling numerous scheduling and routing constraints while aiming to minimise the operat... Read More about Adaptive multiple crossover genetic algorithm to solve workforce scheduling and routing problem.

Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows (2018)
Journal Article

© 2018, The Author(s). An effective and fast hybrid metaheuristic is proposed for solving the pickup and delivery problem with time windows. The proposed approach combines local search, large neighbourhood search and guided ejection search in a novel... Read More about Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows.

An evolutionary strategy with machine learning for learning to rank in information retrieval (2018)
Journal Article

© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Learning to rank (LTR) is one of the problems attracting researchers in information retrieval (IR). The LTR problem refers to ranking the retrieved documents for users in search engines,... Read More about An evolutionary strategy with machine learning for learning to rank in information retrieval.

Randomized heuristics for the Capacitated Clustering Problem (2017)
Journal Article

In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between random... Read More about Randomized heuristics for the Capacitated Clustering Problem.

Solving a large real-world bus driver scheduling problem with a multi-assignment based heuristic algorithm (2017)
Journal Article

The bus driver scheduling problem (BDSP) under study consists in finding a set of duties that covers the bus schedule from a Brazilian public transportation bus company with the objective of minimizing the total cost. A deterministic 2-phase heuristi... Read More about Solving a large real-world bus driver scheduling problem with a multi-assignment based heuristic algorithm.

A technique based on trade-off maps to visualise and analyse relationships between objectives in optimisation problems (2017)
Journal Article

Understanding the relationships between objectives in a multiobjective optimisation problem is important for developing tailored and efficient solving techniques. In particular, when tackling combinatorial optimisation problems with many objectives t... Read More about A technique based on trade-off maps to visualise and analyse relationships between objectives in optimisation problems.

Dynamic programming with approximation function for nurse scheduling (2016)
Journal Article

Although dynamic programming could ideally solve any combinatorial optimization problem, the curse of dimensionality of the search space seriously limits its application to large optimization problems. For example, only few papers in the literature h... Read More about Dynamic programming with approximation function for nurse scheduling.

An application programming interface with increased performance for optimisation problems data (2016)
Journal Article

An optimisation problem can have many forms and variants. It may consider different objectives, constraints, and variables. For that reason, providing a general application programming interface (API) to handle the problem data efficiently in all sce... Read More about An application programming interface with increased performance for optimisation problems data.

Decomposition techniques with mixed integer programming and heuristics for home healthcare planning (2016)
Journal Article

We tackle home healthcare planning scenarios in the UK using decomposition methods that incorporate mixed integer programming solvers and heuristics. Home healthcare planning is a difficult problem that integrates aspects from scheduling and routing.... Read More about Decomposition techniques with mixed integer programming and heuristics for home healthcare planning.

Hyper-volume evolutionary algorithm (2016)
Journal Article

We propose a multi-objective evolutionary algorithm (MOEA), named the Hyper-volume Evolutionary Algorithm (HVEA). The algorithm is characterised by three components. First, individual fitness evaluation depends on the current Pareto front, specifical... Read More about Hyper-volume evolutionary algorithm.

Term frequency with average term occurrences for textual information retrieval (2015)
Journal Article

In the context of Information Retrieval (IR) from text documents, the term-weighting scheme (TWS) is a key component of the matching mechanism when using the vector space model (VSM). In this paper we propose a new TWS that is based on computing the... Read More about Term frequency with average term occurrences for textual information retrieval.

A hybrid GRASP-VNS for Ship Routing and Scheduling Problem with Discretized Time Windows (2015)
Journal Article

This paper addresses the Ship Routing and Scheduling Problem with Discretized Time Windows. Being one of the most relevant and challenging problems faced by decision makers from shipping companies, this tramp shipping problem lies in determining the... Read More about A hybrid GRASP-VNS for Ship Routing and Scheduling Problem with Discretized Time Windows.

Workforce scheduling and routing problems: literature survey and computational study (2014)
Journal Article

In the context of workforce scheduling, there are many scenarios in which personnel must carry out tasks at different locations hence requiring some form of transportation. Examples of these type of scenarios include nurses visiting patients at home,... Read More about Workforce scheduling and routing problems: literature survey and computational study.

A heuristic algorithm based on multiassignment procedures for nurse scheduling (2014)
Journal Article

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses? preferences and m... Read More about A heuristic algorithm based on multiassignment procedures for nurse scheduling.

Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems (2013)
Journal Article

This paper presents the first investigation on applying a particle swarm optimization (PSO) algorithm to both the Steiner tree problem and the delay constrained multicast routing problem. Steiner tree problems, being the underlining models of many ap... Read More about Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems.

Overview of telematics-based prognostics and health management systems for commercial vehicles (2013)
Journal Article

Prognostics and Health Management/Monitoring (PHM) are methods to assess the health condition and reliability of systems for the purpose of maximising operational reliability and safety. Recently, PHM systems are emerging in the automotive industry.... Read More about Overview of telematics-based prognostics and health management systems for commercial vehicles.

An evolutionary non-Linear great deluge approach for solving course timetabling problems (2012)
Journal Article

The aim of this paper is to extend our non-linear great deluge algorithm into an evolutionary approach by incorporating a population and a mutation operator to solve the university course timetabling problems. This approach might be seen as a variati... Read More about An evolutionary non-Linear great deluge approach for solving course timetabling problems.

An adaptive evolutionary multi-objective approach based on simulated annealing (2011)
Journal Article

A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA... Read More about An adaptive evolutionary multi-objective approach based on simulated annealing.