Over the last years, there has been a growing interest in the idea of combining the two techniques of Constraint Programming and Mixed Integer Programming. The idea is appealing, because the techniques are very similar in that they both rely on the idea of branching and are principally able to solve almost the same class of problems, on the other hand the efficiency of the techniques on certain...

Mixed-integer programming (MIP) technology offers a generic way of formulating and solving combinatorial optimization problems. While generally reliable, state-of-the-art MIP solvers base many crucial decisions on hand-crafted heuristics, largely ignoring common patterns within given instance distribution the problem interest. Here, we propose MIP-GNN, general framework for enhancing such with ...

Recently, we compared the performance of mixed-integer programming (MIP), constraint programming (CP), and constraint integer programming (CIP) to a state-of-the-art logic-based Benders manual decomposition (LBBD) for a resource allocation/scheduling problem. For a simple linear relaxation, the LBBD and CIP models deliver comparable performance with MIP also performing well. Here we show that a...

Hubs are facilities to collect arrange and distribute commodities in telecommunication networks, cargo delivery systems, etc. In this paper, an uncapacitated phub center problem in case of single allocation and also multiple allocation will be introduced in which travel times or transportation costs are considered as fuzzy parameters. Then, by proposing new methods, the presented problem is con...

In this paper we consider a generalization of the Markowitz's Mean-Variance model under linear transaction costs and cardinality constraints. The cardinality constraints are used to limit the number of assets in the optimal portfolio. The generalized model is formulated as a mixed integer quadratic programming (MIP) problem. The purpose of this paper is to investigate a continuous approach base...

This paper presents the review of past studies concerning mathematical models for rescheduling passenger railway services, as part of delay management in the occurrence of railway disruption. Many past mathematical models highlighted were aimed at minimizing the service delays experienced by passengers during service disruptions. Integer programming (IP) and mixed-integer programming (MIP) mode...

We define difficult optimization problems as problems which cannot be solved to optimality or to any guaranteed bound by any standard solver within a reasonable time limit. The problem class we have in mind are mixed integer programming (MIP) problems. Optimization and especially mixed integer optimization is often appropriate and frequently used to model real world optimization problems. While...

In this paper we present a rather new approach to apply mixed-integer optimization to the cryptanalysis of cryptographic primitives. We focus on the stream cipher Trivium, that has been recommended by the eSTREAM stream cipher project, and the lightweight block cipher Ktantan. Using these examples we explain how the problem of solving a non-linear multivariate Boolean equation system can be for...

We present the application of Genetic Programming (GP) in Branch and Bound (B&B) based Mixed Integer Linear Programming (MIP). The hybrid architecture introduced employs GP as a node selection expression generator: a GP run, embedded into the B&B process, exploits the characteristics of the particular MIP problem being solved, evolving a problem-specific node selection method. The evolved metho...