Most organizations already use to a certain extent effectively descriptive analytics to understand past events. Fewer attempts through predictive analytics the anticipation of scenarios and estimation of trends, and only a minority triggers great or clever recommendations based on prescriptive analytics.
The necessary change of companies’ mindset regarding the use of optimization models and business decision support systems, requires more than just appropriate technology, people and processes. It requires a proper change management.
In this talk, we make use of a few successful and unsuccessful business analytics projects related to ONPCE, as well as recent developments in prescriptive analytics, to draw some guidelines and best practices of this field.
This talk presents a new model for the exact solution of the compartmentalized knapsack problem, denoted as the strong integer linear model, derived from the (linear) IP formulation by strengthening data, reducing symmetry, and lifting, and also a new pseudo-polynomial heuristic, the heuristic of the pk strong capacities.
In this talk, we present the multimodal hub network design problem with flexible routes. Routes may contain a mix of hub nodes and non-hub nodes, but commodity transfers happen only at installed hubs. While transportation costs are flow-dependent, scale economies stem from the transport technology chosen to operate the routes. This problem addresses an important modeling issue raised in 2006 by Alf Kimms and somehow overlooked by the literature. A mixed-integer mathematical program and two metaheuristics based on the adaptive large neighborhood search paradigm are used to solve the problem.