A system to integrate unstructured and semistructured information resources: an application in an innovation design process

A system that integrates different tools, from multicriteria analysis and mathematical programming but also cognitive and social psychology, can be proposed to cope with complexities and uncertainties that generate criticality in the socio technical approach. The purpose of this paper is to examine the potentialities of this system, above all in terms of information fusion and use in various contexts, and to propose an application in relation to an industrial project, in order to support the conceptual phase of the design processr

Matheuristics for Combinatorial Optimization Problems:Applications to Services and Production Systems

Many problems arising in different areas such as production or distribution of goods and services are combinatorial optimization problems (COPs). Many examples can be made for all areas: • Production Scheduling (flow shop, job shop, open shop, etc.) • Resource Management (production factors, human capital, lot sizing etc.) • Logistics (warehouses, distribution, location, etc.) • Finance (portfolio management, risk management, etc.) These problems are interesting because of their relevant practical importance but are also well known to be difficult to solve. This difficulty and, at the same time, the fact that they are concrete and important problems, have led to a large number of solution techniques for COPs. The solution techniques for solving them are traditionally split into exact (mostly based on the optimal solution of the integer programming formulation of the real problem) and heuristic algorithms. Recently a new wave has rapidly grown in the community of researchers, the hybridization of these two approaches, the so called Matheuristics which rely on the idea of exploiting the best of the two, leading to a very large scale neighborhood search based on mathematical programming. While for the combination of heuristic procedures there exists a wide literature, matheuristics are still in development. The Thesis, beyond an introduction on that new approach, presents several different examples and results of such matheuristics on a variety of test instances. Finally some conclusion from the performed experiments and trajectories for future research are draw

Searching for a cycle with maximum coverage in undirected graphs

The present contribution considers the problem of identifying a simple cycle in an undirected graph such that the number of nodes in the cycle or adjacent to it, is maximum. This problem is denoted as the Maximum Covering Cycle Problem (MCCP) and it is shown to be NP-complete. We present an iterative procedure that, although it cannot be shown to be polynomial, yields (in practice) high-quality solutions within reasonable time on graphs of moderate density.status: publishe

A Matheuristic Approach for the Total Completion Time Two-Machines Permutation Flow Shop Problem

This paper deals with the total completion time 2-machines flow shop problem. We present a so-called matheuristic post processing procedure that improves the objective function value with respect to the solutions provided by state of the art procedures. The proposed procedure is based on the positional completion times integer programming formulation of the problem with O(n 2) variables and O(n) constraints

A hybrid heuristic approach for single machine scheduling with release times

International audienceIn this work we consider the well-known one-machine total completion time sequencing problem subject to release times. We present a very large scale neighborhood search heuristic based on mathematical programming. This heuristic makes use of the positional completion time formulation of the problem in which valid inequalities are added. The proposed procedure compares favorably with the state of the art heuristic

An exact approach for the 0-1 knapsack problem with setups

We consider the 0-1 Knapsack Problem with Setups. We propose an exact approach which handles the structure of the ILP formulation of the problem. It relies on partitioning the variables set into two levels and exploiting this partitioning. The proposed approach favorably compares to the algorithms in literature and to solver CPLEX 12.5 applied to the ILP formulation. It turns out to be very effective and capable of solving to optimality, within limited CPU time, all instances with up to 100,000 variables