Lower bounds for the earliness-tardiness scheduling problem on single and parallel machines

This paper addresses the parallel machine scheduling problem in which the jobs have distinct due dates with earliness and tardiness costs. New lower bounds are proposed for the problem, they can be classed into two families. First, two assignment-based lower bounds for the one-machine problem are generalized for the parallel machine case. Second, a time-indexed … Read more

Proximal-ACCPM: a versatile oracle based optimization method

Oracle Based Optimization (OBO) conveniently designates an approach to handle a class of convex optimization problems in which the information pertaining to the function to be minimized and/or to the feasible set takes the form of a linear outer approximation revealed by an oracle. We show, through three representative examples, how difficult problems can be … Read more

A Piecewise Linearization Framework for Retail Shelf Space Management Models

Managing shelf space is critical for retailers to attract customers and to optimize profit. This paper develops a shelf space allocation optimization model that explicitly incorporates essential in-store costs and considers space- and cross-elasticities. The resultant model maximizes a signomial objective function over linear and bilinear constraints in mixed-integer variables. We propose a piecewise linearization … Read more

Survivable IP network design with OSPF routing

Internet protocol (IP) traffic follows rules established by routing protocols. Shortest path based protocols, such as Open Shortest Path First (OSPF), direct traffic based on arc weights assigned by the network operator. Each router computes shortest paths and creates destination tables used for routing flow on the shortest paths. If a router has multiple outgoing … Read more

Domination between traffic matrices

A traffic matrix $D^1$ dominates a traffic matrix $D^2$ if $D^2$ can be routed on every (capacitated) network where $D^1$ can be routed. We prove that $D^1$ dominates $D^2$ if and only if $D^1$, considered as a capacity vector, supports $D^2$. We show several generalizations of this result. CitationCentro Vito Volterra, Universita’ di Roma Tor … Read more

Reduction Tests for the Prize-Collecting Steiner Problem

The Prize-Collecting Steiner Problem (PCSP) is a generalization of the classical Steiner Problem in Graphs (SPG) where instead of terminal vertices that must be necessarily connected, one have profits associated to the vertices that must be balanced against the connection costs. This problem is gaining much attention in the last years due to its practical … Read more

Note: A Graph-Theoretical Approach to Level of Repair Analysis

Level of Repair Analysis (LORA) is a prescribed procedure for defence logistics support planning. For a complex engineering system containing perhaps thousands of assemblies, sub-assemblies, components, etc. organized into several levels of indenture and with a number of possible repair decisions, LORA seeks to determine an optimal provision of repair and maintenance facilities to minimize … Read more

Robust Profit Opportunities in Risky Financial Portfolios

For risky financial securities with given expected return vector and covariance matrix, we propose the concept of a robust profit opportunity in single and multiple period settings. We show that the problem of finding the “most robust” profit opportunity can be solved as a convex quadratic programming problem, and investigate its relation to the Sharpe … Read more

Leader-Follower Equilibria for Electric Power and NO_x Allowances Markets

This paper investigates the ability of the largest producer in an electricity market to manipulate both the electricity and emission allowances markets to its advantage. A Stackelberg game to analyze this situation is constructed in which the largest firm plays the role of the leader, while the medium-sized firms are treated as Cournot followers with … Read more

Interior point methods for large-scale linear programming

We discuss interior point methods for large-scale linear programming, with an emphasis on methods that are useful for problems arising in telecommunications. We give the basic framework of a primal-dual interior point method, and consider the numerical issues involved in calculating the search direction in each iteration, including the use of factorization methods and/or preconditioned … Read more