Publications

In the Netherlands and Flanders, vocational interest inventories are frequently used to address (study) career dilemmas. In contrast to their popularity in practice, in the Dutch language region, there is relatively little research looking at vocational interest(s) (inventories). This artide introduces the Spherical Model of Vocational Interests and the Dutch translation of the Personal Globe Inventory(PGI; Tracey, 2002), a measure for this ...

The inherent uncertainty in supply chain systems compels managers to be more perceptive to the stochastic nature of the systems' major parameters, such as suppliers' reliability, retailers' demands, and facility production capacities. To deal with the uncertainty inherent to the parameters of the stochastic supply chain optimization problems and to determine optimal or close to optimal policies, many approximate deterministic equivalent models ...

Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers ...

Objective
Central sensitization is present in different pain conditions, including chronic whiplash-associated disorders. In the absence of a gold standard method of assessment to determine the presence of central sensitization, quantitative sensory testing is currently understood as an optimal proxy. Laboratory sensory testing is, however, not feasible in clinical practice, and the Central Sensitization Inventory was developed as an ...

Inventory Routing Problem (IRP) combines the two sub problems -inventory management and transport management- into one integrated optimization model, with the objective of reducing costs and assuring the promised service to the retailer. Every retailer has a limited capacity inventory location to store stocks so they are able to satisfy the demand until the next replenishment. The supplier decides the delivery time, the size of delivery and the ...

This chapter discusses the issue of integrating inventory and distribution optimization together with game theory to effectively manage supply networks. Inventory and distribution simultaneously optimization is a challenging problem aiming at coordinating decisions related to inventory management with those related to transportation scheduling. This problem is known as the inventory routing problem (IRP) and is an underlying optimization model ...

Classic inventory models use average cost functions. It is generally accepted that these models should account for the time value of money. They do so not by considering the timing of cash-flows, but by including opportunity costs. The Net Present Value (NPV) framework has long been used to compare these models with. We formalise NPV Equivalence Analysis (NPVEA) under various payment structures, and apply it to a few classic inventory models. ...

Deep reinforcement learning (DRL) has proven to be an effective, general-purpose technology to develop ‘good’ replenishment policies in inventory management. We show how transfer learning from existing, well-performing heuristics may stabilize the training process and improve the performance of DRL in inventory control. While the idea is general, we specifically implement potential-based reward shaping to a deep Q-network algorithm to manage ...