A MILP Approach to DRAM Access Worst-Case Analysis

The Dynamic Random Access Memory (DRAM) is among the major points of contention in multi-core systems. We consider a challenging optimization problem arising in worst-case performance analysis of systems architectures: computing the worst-case delay (WCD) experienced when accessing the DRAM due to the interference of contending requests. The WCD is a crucial input for micro-architectural … Read more

Fleet planning under demand uncertainty: a reinforcement learning approach

This work proposes a model-free reinforcement learning approach to learn a long-term fleet planning problem subjected to air-travel demand uncertainty. The aim is to develop a dynamic fleet policy that adapts over time by intermediate assessments of the states. A Deep Q-network is trained to estimate the optimal fleet decisions based on the airline and … Read more

Solving the Traveling Salesman Problem with release dates via branch-and-cut

In this paper we study the Traveling Salesman Problem with release dates (TSP-rd) and completion time minimization. The TSP-rd considers a single vehicle and a set of customers that must be served exactly once with goods that arrive to the depot over time, during the planning horizon. The time at which each requested good arrives … Read more

Maintenance Optimization of Wagons Mix

This work proposes to create a tool for support for cost reduction in wagon maintenance through the distribution of the annual plan in workshops. The distribution depends on the type of wagon, the scope of the maintenance service that each workshop serves, and the capacity that is supported by the workshops. This plan is a … Read more

Price Optimization with Practical Constraints

In this paper, we study a retailer price optimization problem which includes the practical constraints: maximum number of price changes and minimum amount of price change (if a change is recommended). We provide a closed-form formula for the Euclidean projection onto the feasible set defined by these two constraints, based on which a simple gradient … Read more

A Chance-Constrained Two-Echelon Vehicle Routing Problem with Stochastic Demands

Two-echelon distribution systems are often considered in city logistics to maintain economies of scale and satisfy the emission zone requirements in the cities. In this work, we formulate the two-echelon vehicle routing problem with stochastic demands as a chance-constrained stochastic optimization problem, where the total demand of the customers in each second-echelon route should fit … Read more

A support tool for planning classrooms considering social distancing between students

In this paper, we present the online tool salaplanejada.unifesp.br developed to assist the layout planning of classrooms considering the social distance in the context of the COVID-19 pandemic. We address both the allocation problem in rooms where seats are fixed as well as the problem in rooms where seats can be moved freely. For the … Read more

Efficient Prices under Uncertainty and Non-Convexity

Operators of organized wholesale electricity markets attempt to form prices in such a way that the private incentives of market participants are consistent with a socially optimal commitment and dispatch schedule. In the U.S. context, several competing price formation schemes have been proposed to address the non-convex production cost functions characteristic of most generation technologies. … Read more

On Convex Lower-Level Black-Box Constraints in Bilevel Optimization with an Application to Gas Market Models with Chance Constraints

Bilevel optimization is an increasingly important tool to model hierarchical decision making. However, the ability of modeling such settings makes bilevel problems hard to solve in theory and practice. In this paper, we add on the general difficulty of this class of problems by further incorporating convex black-box constraints in the lower level. For this … Read more

The Integrated Lot Sizing and Cutting Stock Problem in an Automotive Spring Factory

In this paper, a manufacturer of automotive springs is studied in order to reduce inventory costs and losses in the steel bar cutting process. For that, a mathematical model is proposed, focused on the short term decisions of the company, and considering parallel machines and operational constraints, besides the demand, inventory costs and limits for … Read more