Facing supply uncertainty of bulky wastes, the capacitated multi-product stochastic network design model for bulky waste recycling is proposed in this paper. The objective of this model is to minimize the first-stage total fixed costs and the expected value of the second-stage variable costs. The possibility of operation costs and transportation costs for bulky waste recycling is considered ...

We introduce a new concept in column generation for handling complex large scale optimization problems, called two-stage column generation, where columns for the compact and extensive formulation are simultaneously generated. The new framework is specifically conceived for tackling complex problems that cannot be efficiently solved by standard column generation and exploits the relationship bet...

Since the advent of osseointegration approximately 20 years ago, there has been a great deal of scientific data developed on two-stage integrated implant systems. Although these implants were originally designed primarily for fixed prostheses in the mandibular arch, they have been used in partially dentate patients, in patients needing overdentures, and in single-tooth restorations. In addition...

We introduce and characterize a new class of bargaining solutions: those which can be obtained by sequentially applying two binary relations to eliminate alternatives. As a by-product we obtain as a particular case a partial characterization result by Zhou (Econometrica, 1997) of an extension of the Nash axioms and solution to domains including non-convex problems, as well as a complete charact...

In this paper, we present a novel two-stage metric learning algorithm. We first map each learning instance to a probability distribution by computing its similarities to a set of fixed anchor points. Then, we define the distance in the input data space as the Fisher information distance on the associated statistical manifold. This induces in the input data space a new family of distance metric ...

We study two-stage choice procedures in which the decision maker first preselects the alternatives whose values according to a criterion pass a menu-dependent threshold and then maximizes a second criterion to narrow the selection further. This framework overlaps with several existing models that have various interpretations and impose various additional restrictions on behavior. We show that t...

In seismic data processing, deconvolution plays a very important role because it permits to increase the temporal resolution of seismic sections and to equalize sources. The deconvolution problem when the wavelet is known is an ill-posed problem that can be tackled via regularization methods. However, the seismic source wavelet is unknown and therefore, it must be estimated from the data prior ...

The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony s...

This paper presents the application of Two-Stage Programming (2sp) for developing error-free paral-lel/distributed applications through automatic verii-cation of computed results with respect to a given speciication. The presentation focuses the case study of the parallel block-striped partitioning variant of Prim's algorithm for nding a minimum spanning tree of a dense graph. We show that the ...