Distributionally Robust Inventory Management with Advance Purchase Contracts

Motivated by the worldwide Covid-19 vaccine procurement, we study an inventory problem with an advance purchase contract which requires all ordering decisions to be committed at once. In reality, not only the demand is uncertain, but its distribution can also be ambiguous. Hence, we assume that only the mean and the variance are known and … Read more

Distributional robustness and inequity mitigation in disaster preparedness of humanitarian operations

We study a predisaster relief network design problem with uncertain demands. The aim is to determine the prepositioning and reallocation of relief supplies. Motivated by the call of the International Federation of Red Cross and Red Crescent Societies (IFRC) to leave no one behind, we consider three important practical aspects of humanitarian operations: shortages, equity, … Read more

Optimal Robust Policy for Feature-Based Newsvendor

We study policy optimization for the feature-based newsvendor, which seeks an end-to-end policy that renders an explicit mapping from features to ordering decisions. Unlike existing works that restrict the policies to some parametric class which may suffer from sub-optimality (such as affine class) or lack of interpretability (such as neural networks), we aim to optimize … Read more

The probabilistic travelling salesman problem with crowdsourcing

We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer’s own vehicle. We formalise … Read more

The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery: A Benders decomposition approach

Crowd-shipping is an emergent solution to avoid the negative effects caused by the growing demand for last-mile delivery services. Previous research has studied crowd-shipping typically at an operational planning level. However, the study of support infrastructure within a city logistics framework has been neglected, especially from a strategic perspective. We investigate a crowd-sourced last-mile parcel … Read more

Improved Branch-and-Cut for the Inventory Routing Problem Based on a Two-Commodity Flow Formulation

This paper examines the Inventory Routing Problem (IRP) with Maximum Level inventory policy. The IRP is a broad class of hard to solve problems with numerous practical applications in the field of freight transportation and logistics. A supplier is responsible for determining the timing and the quantity of replenishment services offered to a set of … Read more

Bicriteria approaches for an optimal balance between resilience and cost-effectiveness of supply chains

In supply chain optimization multiple objectives are considered simultaneously, for example to increase resilience and reduce costs. In this paper we discuss the corresponding bicriteria problems to find a good balance between these two objectives. We give a general model for supply chain resilience that integrates strategic decisions with the operational level. This modular model … Read more

A decomposition resolution approach for a production inventory- distribution-routing problem

The aim of this study is to develop a solution to the problem of distribution of goods proposed by the Mathematical Competitive Game 2017-2018, jointly organized by the French Federation of Mathematical Games and Mathematical Modelling Company. Referred to as a production-inventory-distribution-routing problem (PIDRP), it is an NP-hard combinatorial optimization problem, which received the least … Read more

Evaluating on-demand warehousing via dynamic facility location models

On-demand warehousing platforms match companies with underutilized warehouse and distribution capabilities with customers who need extra space or distribution services. These new business models have unique advantages, in terms of reduced capacity and commitment granularity, but also have different cost structures compared to traditional ways of obtaining distribution capabilities. This research is the first quantitative … Read more

Estimation of Marginal Cost to Serve Individual Customers

This paper proposes a scenario sampling-based framework to estimate the expected incremental routing cost required so as to incorporate a target customer into an inherently stochastic supply chain network. Inspired from a real-life setting arising in the distribution of industrial gases, we demonstrate our framework and elucidate the quality of the marginal cost estimates it … Read more