Research Repository

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An agent based modelling approach for the office space allocation problem (2018)
Conference Proceeding
Dediu, A., Landa-Silva, D., & Siebers, P. (2018). An agent based modelling approach for the office space allocation problem

This paper describes an agent based simulation model to create solutions for the office space allocation (OSA) problem. OSA is a combinatorial optimization problem concerned with the allocation of available office space to a set of entities such as p... Read More

Lookahead policy and genetic algorithm for solving nurse rostering problems (2018)
Conference Proceeding
Peng, S., & Dario, L. (2018). Lookahead policy and genetic algorithm for solving nurse rostering problems. In n/a

Previous research has shown that value function approximation in dynamic programming does not perform too well when tackling difficult combinatorial optimisation problem such as multi-stage nurse rostering. This is because the large action space that... Read More

Adaptive multiple crossover genetic algorithm to solve Workforce Scheduling and Routing Problem (2018)
Journal Article
Algethami, H., Martinez-Gavara, A., & Landa-Silva, D. (2018). Adaptive multiple crossover genetic algorithm to solve Workforce Scheduling and Routing Problem. Journal of Heuristics, doi:10.1007/s10732-018-9385-x. ISSN 1381-1231

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

A genetic algorithm with composite chromosome for shift assignment of part-time employees (2018)
Conference Proceeding
Xue, N., Landa-Silva, D., Triguero, I., & Figueredo, G. P. (2018). A genetic algorithm with composite chromosome for shift assignment of part-time employees

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is... Read More

An efficient application of goal programming to tackle multiobjective problems with recurring fitness landscapes (2018)
Journal Article
Pinheiro, R. L., Landa-Silva, D., Laesanklang, W., & Constantino, A. A. (in press). An efficient application of goal programming to tackle multiobjective problems with recurring fitness landscapes. Communications in Computer and Information Science,

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 problems is often a difficult task even... Read More

Using goal programming on estimated Pareto fronts to solve multiobjective problems (2018)
Conference Proceeding
Pinheiro, R. L., Landa-Silva, D., Laesanklang, W., & Constantino, A. A. (2018). Using goal programming on estimated Pareto fronts to solve multiobjective problems

Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems. Such problems are common in real-world applications where decision-makers need to assess multiple... Read More

Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows (2018)
Journal Article
Curtois, T., Landa-Silva, D., Qu, Y., & Laesanklang, W. (2018). Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows. Euro Journal of Transportation and Logistics, 7(2), doi:10.1007/s13676-017-0115-6

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 way to exploit the ben... Read More

An evolutionary strategy with machine learning for learning to rank in information retrieval (2018)
Journal Article
Ibrahim, O. A. S., & Landa-Silva, D. (2018). An evolutionary strategy with machine learning for learning to rank in information retrieval. Soft Computing, 22(10), doi:10.1007/s00500-017-2988-6

Learning to Rank (LTR) is one of the problems in Information Retrieval (IR) that nowadays attracts attention from researchers. The LTR problem refers to ranking the retrieved documents for users in search engines, question answering and product recom... Read More

Fuzzy C-means-based scenario bundling for stochastic service network design (2017)
Conference Proceeding
Jiang, X., Bai, R., Landa-Silva, D., & Aickelin, U. (2017). Fuzzy C-means-based scenario bundling for stochastic service network design

Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging algorithm (PHA) is a decomposition method for solvi... Read More

Approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem (2017)
Conference Proceeding
Shi, P., & Landa-Silva, D. (2017). Approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem

An approximate dynamic programming that incorporates a combined policy, value function approximation and lookahead policy, is proposed. The algorithm is validated by applying it to solve a set of instances of the nurse rostering problem tackled as a... Read More

Multi-start methods for the capacitated clustering problem (2017)
Conference Proceeding
Martinez-Gavara, A., Campos, V., Landa-Silva, D., & Marti, R. (2017). Multi-start methods for the capacitated clustering problem

In this work, 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 randomi... Read More

Randomized heuristics for the Capacitated Clustering Problem (2017)
Journal Article
Martinez-Gavara, A., Landa-Silva, D., Campos, V., & Marti, R. (2017). Randomized heuristics for the Capacitated Clustering Problem. Information Sciences, 417, doi:10.1016/j.ins.2017.06.041

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

Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem (2017)
Conference Proceeding
Algethami, H., & Landa-Silva, D. (2017). Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem

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 total opera... Read More

Solving a large real-world bus driver scheduling problem with a multi-assignment based heuristic algorithm (2017)
Journal Article
Constantino, A. A., de Mendonca, C. F., de Araujo, S. A., Landa-Silva, D., Calvi, R., & dos Santos, A. F. (2017). Solving a large real-world bus driver scheduling problem with a multi-assignment based heuristic algorithm. Journal of Universal Computer Science, 23(5),

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

ES-Rank: evolution strategy learning to rank approach (2017)
Conference Proceeding
Ibrahim, O. A. S., & Landa-Silva, D. (2017). ES-Rank: evolution strategy learning to rank approach

Learning to Rank (LTR) is one of the current problems in Information Retrieval (IR) that attracts the attention from researchers. The LTR problem is mainly about ranking the retrieved documents for users in search engines, question answering and prod... Read More

A technique based on trade-off maps to visualise and analyse relationships between objectives in optimisation problems (2017)
Journal Article
Pinheiro, R. L., Landa-Silva, D., & Atkin, J. (2017). A technique based on trade-off maps to visualise and analyse relationships between objectives in optimisation problems. Journal of Multi-Criteria Decision Analysis, 24(1-2), doi:10.1002/mcda.1604

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

Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem (2017)
Conference Proceeding
Algethami, H., Landa-Silva, D., & Martinez-Gavara, A. (2017). Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem

The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including cust... Read More

Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations (2017)
Conference Proceeding
Curtois, T., Laesanklang, W., Landa-Silva, D., Mesgarpour, M., & Qu, Y. (2017). Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations

This paper gives an overview of research work in progress within the COSLE (Collaborative Optimisation in a Shared Logistics Environment) project between the University of Nottingham and Microlise Ltd. This is an R&D project that seeks to develop opt... Read More

Dynamic programming with approximation function for nurse scheduling (2016)
Journal Article
Shi, P., & Landa-Silva, D. (2016). Dynamic programming with approximation function for nurse scheduling. Lecture Notes in Artificial Intelligence, 10122, doi:10.1007/978-3-319-51469-7_23

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

An application programming interface with increased performance for optimisation problems data (2016)
Journal Article
Pinheiro, R. L., Landa-Silva, D., Qu, R., Constantino, A. A., & Yanaga, E. (in press). An application programming interface with increased performance for optimisation problems data. Journal of Management Analytics, 3(4), doi:10.1080/23270012.2016.1233514

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