The increasing frequency of destructive wild land fires, with a consequent loss of life and property, has led to fire and land management agencies initiating extensive fuel management programs. This involves long-term scheduling of the location of fuel reduction activities such as prescribed burning or mechanical clearing. In this paper a Mixed Integer Programming (MIP) … Read more
In this paper we mainly focus on optimization of sums of squares of quadratic functions, which we refer to as second-order least-squares problems, subject to convex constraints. Our motivation arises from applications in risk parity portfolio selection. We generalize the setting further by considering a class of nonlinear, non convex functions which admit a (non … Read more
The European emissions trading scheme (EU-ETS) is a cap and trade system that requires the indus- tries participating in the program to obtain allowances to cover their carbon emissions. Energy Intensive Industries claim that this system puts their European plants at an economics disadvantage compared to fa- cilities located outside the EU. As a direct … Read more
In this paper, we combine ideas from machine learning (ML) and operations research and management science (OR/MS) in developing a framework, along with specific methods, for using data to prescribe optimal decisions in OR/MS problems. In a departure from other work on data-driven optimization and reflecting our practical experience with the data available in applications … Read more
In this paper, we investigate the two-period subproblems proposed by Akartunal{\i} et al. (2014) for big-bucket lot-sizing problems, which have shown a great potential for obtaining strong bounds for these problems. In particular, we study the polyhedral structure of the mixed integer sets related to two relaxations of these subproblems for the special case of … Read more
Since the financial crisis of 2007-2009, there has been a renewed interest toward quantifying more appropriately the risks involved in financial positions. Popular risk measures such as variance and value-at-risk have been found inadequate as we now give more importance to properties such as monotonicity, convexity, translation invariance, scale invariance, and law invariance. Unfortunately, the … Read more
In this paper, we propose two block coordinate gradient (BCG) methods for the online convex programming: the BCG method with the cyclic rule and the BCG method with the random rule. The proposed methods solve a low dimensional problem at each iteration, and hence they are efficient for large scale problems. For the proposed methods, … Read more
In 2004 Newman suggested a semidefinite programming relaxation for the Linear Ordering Problem (LOP) that is related to the semidefinite program used in the Goemans-Williamson algorithm to approximate the Max Cut problem. Her model is based on the observation that linear orderings can be fully described by a series of cuts. Newman shows that her … Read more
This paper studies a robust maritime inventory routing problem with time windows and stochastic travel times. One of the novelties of the problem is that the length and placement of the time windows are also decision variables. Such problems arise in the design and negotiation of long-term delivery contracts with customers who require on-time deliveries … Read more
We propose an exact algorithm for the Target Visitation Problem (TVP). The (TVP) is a composition of the Linear Ordering Problem and the Traveling Salesman Problem. It has several military and non-military applications, where two important, often competing factors are the overall distance traveled (e.g. by an unmanned aerial vehicle) and the visiting sequence of … Read more