Yield uncertainty is an important issue in various industries such as agriculture, food, and textile where the production output is reliant on uncontrollable...

Inventory management for slow-moving items is challenging due to their high intermittence and lumpiness. Recent developments in machine learning and computat...

This paper introduces the Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions (HEVRP-NL). This problem involves routing a ...

We study the integration of multi-period assignment, routing, and scheduling of care workers for home health care services. In such a context, it is importa...

Two-stage stochastic programs are a class of stochastic problems where uncertainty is discretized into scenarios, making them amenable to solution approaches...

This paper investigates a variant of the traveling salesman problem (TSP) with speed optimization for a plug-in hybrid electric vehicle (PHEV), simultaneousl...

We investigate a facility location problem with modular capacity under demand uncertainty arising at Hydro-Québec, the largest public utility in Canada. We p...

Seaports are highly vulnerable to climate-change induced events, which makes it necessary for them to invest in climate change adaptation measures to ensure ...

The procurement of freight services is an important element for the supply chain management of a shipper (i.e., a manufacturer or retailer) that sources tran...

Production yield can be highly volatile and uncertain, especially in industries where exogenous and environmental factors such as the climate or raw material...

Binary quadratic programming (BQP) is a class of combinatorial optimization problems comprising binary variables, quadratic objective functions and linear/no...

Berth allocation and pilotage planning are the two most important decisions made by a seaport for serving incoming vessels. Traditionally, the berth allocati...

Scholars and practitioners have long recognised the importance of data-driven operations and supply chain management (OSCM), which typically centres on produ...

This work investigates lot-sizing with component substitution under demand uncertainty. The integration of component substitution with lot-sizing in an uncer...

This paper studies the team orienteering problem, where the arrival time and service time affect the collection of profits. Such interactions result in a non...

We propose a generalized decomposition approach for production planning problems with process configuration decisions. These problems appear in contexts wher...

Dealing with demand uncertainty in multi-item lot sizing problems poses huge challenges due to the inherent complexity. The resulting stochastic formulation...

Significant progress has been made in the field of computer vision, due to the development of supervised machine learning algorithms, which efficiently extra...

Facility networks can be disrupted by, for example, power outages, poor weather conditions, or natural disasters, and the probabilities of these events may b...

We study an integrated process configuration, lot-sizing, and scheduling problem, which appears in a real production environment in the packaging industry. P...