P
Paul R. Drake
Researcher at University of Liverpool
Publications - 37
Citations - 1790
Paul R. Drake is an academic researcher from University of Liverpool. The author has contributed to research in topics: Artificial neural network & Genetic algorithm. The author has an hindex of 19, co-authored 36 publications receiving 1587 citations. Previous affiliations of Paul R. Drake include Cardiff University.
Papers
More filters
Journal ArticleDOI
PSO-based algorithm for home care worker scheduling in the UK
TL;DR: The objectives of this paper are to exploit a systematic approach to improve the existing schedule of home care workers, and to develop the methodology to enable the continuous PSO algorithm to be efficiently applied to this type of problem and all classes of similar problems.
Journal ArticleDOI
Exploring the role of social capital in facilitating supply chain resilience
TL;DR: In this paper, three dimensions of social capital (cognitive, structural and relational) may act as facilitators or enablers of the four formative capabilities for resilience (i.e. flexibility, velocity, visibility, and collaboration).
Book
Condition-based maintenance and machine diagnostics
TL;DR: In this paper, the authors present a survey of condition-based maintenance information systems in the manufacturing domain, focusing on the aspects of maintenance, including basic diagnostic techniques, vibration monitoring, and particle monitoring.
Journal Article
Using the Analytic Hierarchy Process in Engineering Education
TL;DR: The Analytic Hierarchy Process (AHP) as discussed by the authors was introduced into undergraduate and postgraduate student projects to formalise the process of selection of "hard" and "soft" system components.
Journal ArticleDOI
A portfolio model for component purchasing strategy and the case study of two South Korean elevator manufacturers
Dong Myung Lee,Paul R. Drake +1 more
TL;DR: In this paper, a new approach to purchasing portfolio modelling, stemming from Kraljic's matrix, for developing purchasing strategies that are aligned with competitive priorities, is developed to address the weaknesses of existing approaches that are preventing widespread application, especially in SMEs.