This paper investigates a novel two-phase preventive maintenance policy for a single-component
system with an objective of maximizing the revenue generated by the performance-…

Applications of deep transfer learning to intelligent fault diagnosis of machines commonly
assume symmetry among domains: 1) the samples from target machines are balanced across …

The tremendous success of deep learning and transfer learning broadened the scope of
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …

Recent years have witnessed the prominent advancements of deep learning (DL) in the
arsenal of prognostics and health management. However, the prognostic uncertainty problem …

Cloud manufacturing (CMfg) is emerging as an advanced service-oriented manufacturing
model for the manufacturing industry. It is changing the way manufacturing enterprises …

Most of the current successes of deep transfer learning-based fault diagnosis require two
assumptions: 1) the health state set of source machines should overlap that of target machines; …

We consider a multiple-vehicle routing problem with split pick-ups (mVRPSP). This problem
involves multiple suppliers, a single depot, and a fleet of identical capacity trucks …

This paper addresses a hub-and-spoke network problem for railroad freight, where a central
planner is to find transport routes, frequency of service, length of trains to be used, and …

The sheer amount of Municipal Solid Waste (MSW) produced from residential and commercial
activities has posed a big threat to the modern society, especially to large cities by …

We consider the carrier’s optimal bid generation problem in combinatorial auctions for
transportation procurement. Bidders (carriers) employ vehicle routing models to identify sets of …