Robust combinatorial optimization problems under locally budgeted interdiction uncertainty against the objective function and covering constraints

Recently robust combinatorial optimization problems with budgeted interdiction uncertainty affecting cardinality-based constraints or objective were considered by presenting, comparing and experimenting with compact formulations. In this paper we present a compact formulation for the case in which locally budgeted interdiction uncertainty affects the objective function and covering constraints simultaneously. ArticleDownload View PDF

Robust combinatorial optimization problems with knapsack constraints under interdiction uncertainty

We present an algorithm for finding near-optimal solutions to robust combinatorial optimization problems with knapsack constraints under interdiction uncertainty. We incorporate a heuristic for generating feasible solutions in a standard row generation approach. Experimental results are presented for set covering, simple plant location, and min-knapsack problems under a discrete-budgeted interdiction uncertainty set introduced in this … Read more

Absolute regret of implicitly defined sets for combinatorial optimization problems

We consider combinatorial optimization problems with interval uncertainty in the cost vector. Recently a new approach was developed to deal with such uncertainties: instead of a single one absolute robust solution, obtained by solving a min max problem, a set of cardinality predefined and minimal absolute regret, obtained by solving a min max min problem, … Read more

Min max (relative) set-regret combinatorial optimization

We consider combinatorial optimization problems with uncertainty in the cost vector. Recently a novel approach was developed to deal such uncertainties: instead of a single one robust solution, obtained by solving a min max problem, the authors consider a set of solutions obtained by solving a min max min problem. In this new approach the … Read more

Generalized average shadow prices and bottlenecks

We present a generalization of the average shadow price in 0-1-Mixed Integer Linear Programming problems and its relation with bottlenecks including the analysis relative to the coefficients matrix of resource constraints. A mathematical programming approach to find the strategy for investment in resources is presented. CitationEscuela de Computación, Facultad de Ciencias, Universidad Central de VenezuelaArticleDownload … Read more

A parametric programming approach to redefine the global configuration of resource constraints of 0-1-Integer Linear Programming problems.

A mathematical programming approach to deal with the global configuration of resource constraints is presented. A specialized parametric programming algorithm to obtain the pareto set for the biobjective problem that appears to deal with the global configuration for 0-1-Integer Linear Programing problems is presented and implemented. Computational results for Multiconstrained Knapsack problems and Bounded Knapsack … Read more

Mathematical programming approach to tighten a Big-$ formulation

In this paper we present a mathematical programming approach to tighten a Big-$M$ formulation ($P_M$) of a Mixed Integer Problem with Logical Implications ($P$). If $M_0$ is a valid vector (the optimal solutions of $P$ belong to the feasible solutions set of $P_{M_0}$) our procedures find a valid vector $M$ such that $M \leq M_0$. … Read more

Approximating the solution for the multiparametric 0-1-mixed integer linear programming problem with interval data

In this paper we present algorithms to approximate the solution for the multiparametric 0-1-mixed integer linear programming problem relative to the objective function. We consider the uncertainty for the parameters that de fine the cost vector corresponding to a subset of 0-1-variables by assuming that each parameter belongs to a known interval. We suppose that we … Read more