An Integrated Car-and-ride Sharing System for Mobilizing Heterogeneous Travelers with Application in Underserved Communities

The fast-growing carsharing and ride-hailing businesses are generating economic benefits and societal impacts in the modern society. However, both have limitation to cover demand from diverse populations, e.g., travelers in low-income, underserved communities. In this paper, we consider two types of travelers: Type~1 who rent shared cars and Type~2 who need shared rides. We propose … Read more

Multistage stochastic programs with a random number of stages: dynamic programming equations, solution methods, and application to portfolio selection

We introduce the class of multistage stochastic optimization problems with a random number of stages. For such problems, we show how to write dynamic programming equations and detail the Stochastic Dual Dynamic Programming algorithm to solve these equations. Finally, we consider a portfolio selection problem over an optimization period of random duration. For several instances … Read more

Models and algorithms for the robust resource constrained shortest path problem

We study the robust resource constrained shortest path problem (RCSPP) under uncertainty in cost and multiple resource consumption. Contrary to the deterministic RCSPP where the cost and the consumption of resources on an arc are known and fixed, the robust RCSPP models the case where both the cost and the resource consumption are random, and … Read more

Branch-Cut-and-Price for the Vehicle Routing Problem with Time Windows and Convex Node Costs

Two critical yet frequently conflicting objectives for logistics and transportation service companies are improving customer satisfaction and reducing transportation cost. In particular, given a net- work of customer requests with preferred service times, it is very challenging to find vehicle routes and service schedules simultaneously that respect all operating constraints and minimize the total transportation … Read more

Revisiting the Hamiltonian p-median problem: a new formulation on directed graphs and a branch-and-cut algorithm

This paper studies the Hamiltonian p-median problem defined on a directed graph, which consists of finding p mutually disjoint circuits of minimum total cost, such that each node of the graph is included in one of the circuits. Earlier formulations are based on viewing the problem as one resulting from the intersection of two subproblems. … Read more

On stochastic auctions in risk-averse electricity markets with uncertain supply

This paper studies risk in a stochastic auction which facilitates the integration of renewable generation in electricity markets. We model market participants who are risk averse and reflect their risk aversion through coherent risk measures. We uncover a closed-form characterization of a risk-averse generator’s optimal pre-commitment behaviour for a given real-time policy, both with and … Read more

Exact and heuristic algorithms for finding envy-free allocations in food rescue pickup and delivery logistics

Food rescue organizations collect and re-distribute surplus perishable food for hunger relief. We propose novel approaches to address this humanitarian logistics challenge and find envy-free allocations of the rescued food together with least travel cost routes. We show that this food rescue and delivery problem is NP-hard and we present a cutting-plane algorithm based on … Read more

Bounds in multi-horizon stochastic programs

In this paper, we present bounds for multi-horizon stochastic optimization problems, a class of problems introduced in [16] relevant in many industry-life applications tipically involving strategic and operational decisions on two different time scales. After providing three general mathematical formulations of a multi-horizon stochastic program, we extend the definition of the traditional Expected Value problem … Read more

A Benders decomposition method for locating stations in a one-way electric car sharing system under demand uncertainty

We focus on a problem of locating recharging stations in one-way station based electric car sharing systems which operate under demand uncertainty. We model this problem as a mixed integer stochastic program and develop a Benders decomposition algorithm based on this formulation. We integrate a stabilization procedure to our algorithm and conduct a large-scale experimental … Read more

Generalization Bounds for Regularized Portfolio Selection with Market Side Information

Drawing on statistical learning theory, we derive out-of-sample and suboptimal guarantees about the investment strategy obtained from a regularized portfolio optimization model which attempts to exploit side information about the financial market in order to reach an optimal risk-return tradeoff. This side information might include for instance recent stock returns, volatility indexes, financial news indicators, … Read more