Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Dario Landa-Silva"'
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 26, Iss Proc. DCM 2010, Pp 135-146 (2010)
The current investigations 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
Externí odkaz:
https://doaj.org/article/fb3701ee78054610bfcbf38fabdc0c4e
Publikováno v:
Proceedings of the Genetic and Evolutionary Computation Conference Companion.
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 the maj
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f855de750279fe500e94d0703a003194
We present a method for bundling scenarios in a progressive hedging heuristic (PHH) applied to stochastic service network design, where the uncertain demand is represented by a finite number of scenarios. Given the number of scenario bundles, we firs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4145c4ec10077a552b358c3611830c4b
https://eprints.nottingham.ac.uk/64316/1/011510252858MergePDF.pdf
https://eprints.nottingham.ac.uk/64316/1/011510252858MergePDF.pdf
Publikováno v:
CEC
Data preprocessing is a key stage in data mining that allows machine learning algorithms to obtain meaningful insights. Many preprocessing problems such as feature selection or instance selection can be modelled as optimisation/search problems. Evolu
Publikováno v:
Journal of Heuristics. 25:753-792
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
Publikováno v:
Journal of Multi-Criteria Decision Analysis. 24:37-56
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
Publikováno v:
CEC
Inventory forecasting is a key component of effective inventory management. In this work, we utilise hybrid deep learning models for inventory forecasting. According to the highly nonlinear and non-stationary characteristics of inventory data, the mo
Publikováno v:
ICORES
The taste and freshness of perishable foods decrease dramatically with time. Effective inventory management requires understanding of market demand as well as balancing customers needs and references with products’ shelf life. The objective is to a