Outputs (10)

Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem (2017)
Presentation / Conference Contribution
Algethami, H., Landa-Silva, D., & Martinez-Gavara, A. (2017, February). Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem. Presented at 6th International Conference on Operations Research and Enterprise Systems (ICORES 2017), Porto, Portugal

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 about Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem.

Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations (2017)
Presentation / Conference Contribution
Curtois, T., Laesanklang, W., Landa-Silva, D., Mesgarpour, M., & Qu, Y. (2017, February). Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations. Presented at 6th International Conference on Operations Research and Enterprise Systems (ICORES 2017), Porto, Portugal

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 about Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations.

Approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem (2017)
Presentation / Conference Contribution
Shi, P., & Landa-Silva, D. Approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem. Presented at 3rd International Workshop on Machine Learning, Optimization and Big Data (MOD 2017)

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 about Approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem.

Diversity-based adaptive genetic algorithm for a Workforce Scheduling and Routing Problem (2017)
Presentation / Conference Contribution
Algethami, H., & Landa-Silva, D. (2017, June). Diversity-based adaptive genetic algorithm for a Workforce Scheduling and Routing Problem. Presented at 2017 IEEE Congress on Evolutionary Computation (CEC 2017), Donostia, Spain

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 about Diversity-based adaptive genetic algorithm for a Workforce Scheduling and Routing Problem.

Multi-start methods for the capacitated clustering problem (2017)
Presentation / Conference Contribution
Martinez-Gavara, A., Campos, V., Landa-Silva, D., & Marti, R. (2017, July). Multi-start methods for the capacitated clustering problem. Presented at 12th Metaheuristics International Conference (MIC 2017), Barcelona, Spain

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 about Multi-start methods for the capacitated clustering problem.

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, https://doi.org/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 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
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 about Solving a large real-world bus driver scheduling problem with a multi-assignment based heuristic algorithm.

ES-Rank: evolution strategy learning to rank approach (2017)
Presentation / Conference Contribution
Ibrahim, O. A. S., & Landa-Silva, D. (2017, April). ES-Rank: evolution strategy learning to rank approach. Presented at 32nd ACM Symposium on Applied Computing (SAC 2017), Marrakech, Morocco

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 about ES-Rank: evolution strategy learning to rank approach.

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), 37-56. https://doi.org/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 about A technique based on trade-off maps to visualise and analyse relationships between objectives in optimisation problems.

An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints (2017)
Presentation / Conference Contribution
Laesanklang, W., Landa-Silva, D., & Castillo-Salazar, J. A. (2016, February). An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints. Presented at ICORES: International Conference on Operations Research and Enterprise Systems, Rome, Italy

This paper presents an investigation into the application of heuristic decomposition and mixed-integer programming to tackle workforce scheduling and routing problems (WSRP) that involve time dependent activities constraints. These constraints refer... Read More about An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints.