An extension of the elimination method for a sparse SOS polynomial

We propose a method to reduce the sizes of SDP relaxation problems for a given polynomial optimization problem (POP). This method is an extension of the elimination method for a sparse SOS polynomial in [Kojima et al., Mathematical Programming] and exploits sparsity of polynomials involved in a given POP. In addition, we show that this … Read more

Multiplically independent word systems

Tressler’s Theorem states that the long-standing Hadamard conjecture (concerning the existence of n by n orthogonal matrices with elements of the same absolute value, for n=4k, k=1,2,…) will be settled if we find n-2 pairwise orthogonal words in a hyperplane of words. In this paper we will prove the counterpart of Tressler’s Theorem: the existence … Read more

Modeling recreational systems using optimization techniques and information technologies

Due to intrinsic complexity and sophistication of decision problems in tourism and recreation, respective decision making processes can not be implemented without making use of modern computer technologies and operations research approaches. In this paper, we review research works on modeling recreational systems. CitationAnnals of Operations Research (accepted)ArticleDownload View PDF

Customized proximal point algorithms for linearly constrained convex minimization and saddle-point problems: a uniform approach

This paper takes a uniform look at the customized applications of proximal point algorithm (PPA) to two classes of problems: the linearly constrained convex minimization problem with a generic or separable objective function and a saddle-point problem. We model these two classes of problems uniformly by a mixed variational inequality, and show how PPA with … Read more

Regularized Sequential Quadratic Programming

We present the formulation and analysis of a new sequential quadratic programming (\SQP) method for general nonlinearly constrained optimization. The method pairs a primal-dual generalized augmented Lagrangian merit function with a \emph{flexible} line search to obtain a sequence of improving estimates of the solution. This function is a primal-dual variant of the augmented Lagrangian proposed … Read more

How tight is the corner relaxation? Insights gained from the stable set problem

The corner relaxation of a mixed-integer linear program is a central concept in cutting plane theory. In a recent paper Fischetti and Monaci provide an empirical assessment of the strength of the corner and other related relaxations on benchmark problems. In this paper we give a precise characterization of the bounds given by these relaxations … Read more

Optimal Toll Design: A Lower Bound Framework for the Asymmetric Traveling Salesman Problem

We propose a framework of lower bounds for the asymmetric traveling salesman problem (TSP) based on approximating the dynamic programming formulation with diff erent basis vector sets. We discuss how several well-known TSP lower bounds correspond to intuitive basis vector choices and give an economic interpretation wherein the salesman must pay tolls as he travels between … Read more

A SIMPLE APPROACH TO OPTIMALITY CONDITIONS IN MINMAX PROGRAMMING

Considering the minmax programming problem, lower and upper subdi erential optimality conditions, in the sense of Mordukhovich, are derived. The approach here, mainly based on the nonsmooth dual objects of Mordukhovich, is completely di erent from that of most of the previous works where generalizations of the alternative theorem of Farkas have been applied. The results obtained … Read more

A Primal-Dual Algorithm for Computing a Cost Allocation in the Core of Economic Lot-Sizing Games

We consider the economic lot-sizing game with general concave ordering cost functions. It is well-known that the core of this game is nonempty when the inventory holding costs are linear. The main contribution of this work is a combinatorial, primal-dual algorithm that computes a cost allocation in the core of these games in polynomial time. … Read more