Algorithmic Approaches for Identifying the Trade-off between Pessimism and Optimism in a Stochastic Fixed Charge Facility Location Problem

We introduce new algorithms to identify the trade-off (TRO) between adopting a distributional belief and hedging against ambiguity when modeling uncertainty in a capacitated fixed charge facility location problem (CFLP). We first formulate a TRO model for the CFLP (TRO-CFLP), which determines the number of facilities to open by minimizing the fixed establishment cost and … Read more

Paving the Way for More Accessible Cancer Care in Low-Income Countries with Optimization

Cancers are a growing cause of morbidity and mortality in low-income countries. Geographic access plays a key role in both timely diagnosis and successful treatment. In areas lacking well-developed road networks, seasonal weather events can lengthen already long travel times to access care. Expanding facilities to offer cancer care is expensive and requires staffing by … Read more

Insights into the computational complexity of the single-source capacitated facility location problem with customer preferences

Single-source capacitated facility location problems are well studied in the operations research literature, yet classic problems often lack practicability by disregarding the customers’ perspective: An authority that assigns customers to open facilities deprives customers from choosing facilities according to their individual preferences. In reality, this can render solutions infeasible, as customers may deviate to their … Read more

Cover-based inequalities for the single-source capacitated facility location problem with customer preferences

The single-source capacitated facility location problem with customer preferences (SSCFLPCP) is known to be strongly NP-hard. Computational tests imply that state-of-the-art solvers struggle with computing exact solutions. In this paper, we contribute two novel preprocessing methods which reduce the size of the considered integer programming formulation, and introduce sets of valid inequalities which decrease the … Read more

Data-Driven Reliable Facility Location Design

We study the reliable (uncapacitated) facility location (RFL) problem in a data-driven environment where historical observations of random demands and disruptions are available. Owing to the combinatorial optimization nature of the RFL problem and the mixed-binary randomness of parameters therein, the state-of-the-art RFL models applied to the data-driven setting either suggest overly conservative solutions, or … Read more

upgrading the network in discrete location problems with customers satisfaction

Generally speaking, in a discrete location problem the decision maker chooses a set of facilities among a finite set of possibilities and decides to which facility each customer will be allocated in order to minimize the allocation cost. However, it is natural to consider the more realistic situation in which customers have their own criterion … Read more

Cooperative locker locations games

More and more people order products online and have parcels delivered to their homes. This leads to more congestion, negatively impacting the environment, public health, and safety. Carriers can use parcel lockers to consolidate and serve their customers to reduce these negative impacts. The implementation of a locker network can, however, be financially challenging. To … Read more

Distributionally Robust Disaster Relief Planning under the Wasserstein Set

We study a two-stage natural disaster management problem modeled as a stochastic program, where the first stage consists of a facility location problem, deciding where to open facilities and pre-allocate resources such as medical and food kits, and the second stage is a fixed-charge transportation problem, routing resources to affected areas after observing a disaster. … Read more

Distributionally Robust Facility Location with Bimodal Random Demand

In this paper, we consider a decision-maker who wants to determine a subset of locations from a given set of candidate sites to open facilities and accordingly assign customer demand to these open facilities. Unlike classical facility location settings, we focus on a new setting where customer demand is bimodal, i.e., display, or belong to, … Read more

Approximate Submodularity and Its Implications in Discrete Optimization

Submodularity, a discrete analog of convexity, is a key property in discrete optimization that features in the construction of valid inequalities and analysis of the greedy algorithm. In this paper, we broaden the approximate submodularity literature, which so far has largely focused on variants of greedy algorithms and iterative approaches. We define metrics that quantify … Read more