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This paper examines how to plan multi-period assortments when customer utility depends on historical assortments. We formulate this problem as a nonlinear integer programming model and show it is NP-hard in the presence of a negative…

Optimization and Control · Mathematics 2025-04-09 Taotao He , Yating Zhang , Huan Zheng

We present a conceptual framework for the dynamic traffic resources allocation problem in a situation of elastic demand among customers. We introduce an activity-based model to express customers' successive actions and transfers in order to…

Computer Science and Game Theory · Computer Science 2018-06-29 Keiichiro Hayakawa , Eiji Hato

We address the problem of locating facilities on the $[0,1]$ interval based on reports from strategic agents. The cost of each agent is her distance to the closest facility, and the global objective is to minimize either the maximum cost of…

Computer Science and Game Theory · Computer Science 2017-01-04 Iddan Golomb , Christos Tzamos

In this paper, we study a dynamic pickup and delivery problem with docking constraints. There is a homogeneous fleet of vehicles to serve pickup-and-delivery requests at given locations. The vehicles can be loaded up to their capacity,…

Optimization and Control · Mathematics 2025-01-10 Markó Horváth , Tamás Kis , Péter Györgyi

The Maximal Covering Location Problem (MCLP) is a classical location problem where a company maximizes the demand covered by placing a given number of facilities, and each demand node is covered if the closest facility is within a…

Optimization and Control · Mathematics 2024-09-10 Concepción Domínguez , Ricardo Gázquez , Juan Miguel Morales , Salvador Pineda

We study the warehouse problem, arising in the area of inventory management and production planning. Here, a merchant wants to decide an optimal trading policy that computes quantities of a single commodity to purchase, store and sell…

Data Structures and Algorithms · Computer Science 2024-01-22 Ishan Bansal , Oktay Günlük

Algorithms with predictions have attracted much attention in the last years across various domains, including variants of facility location, as a way to surpass traditional worst-case analyses. We study the $k$-facility location mechanism…

Computer Science and Game Theory · Computer Science 2024-03-20 Zohar Barak , Anupam Gupta , Inbal Talgam-Cohen

The paper presents a new approach to solve multifacility location problems, which is based on mixed integer programming and algorithms for minimizing differences of convex (DC) functions. The main challenges for solving the multifacility…

Optimization and Control · Mathematics 2020-02-05 Anuj Bajaj , Boris Mordukhovich , Nguyen Mau Nam , Tuyen Tran

In this paper, we consider the multiple probabilistic covering location problem (MPCLP), which attempts to open a fixed number of facilities to maximize the total covered customer demand under a joint probabilistic coverage setting. We…

Optimization and Control · Mathematics 2025-11-24 Yan-Ru Wang , Wei-Kun Chen , Ivana Ljubić

We introduce in this paper a new variant of a location routing problem, to decide, the number and location of drop-off points to install based on the demands of a set of pick-up points, according to a given set-up budget for installing…

Optimization and Control · Mathematics 2025-05-09 Maria Albareda-Sambola , Víctor Blanco , Yolanda Hinojosa

Line planning in public transport is the strategic problem of selecting lines and their operating frequencies. This problem is important as it defines the passenger service, based on available connections and expected travel times, and…

We consider the classic Facility Location problem on planar graphs (non-uniform, uncapacitated). Given an edge-weighted planar graph $G$, a set of clients $C\subseteq V(G)$, a set of facilities $F\subseteq V(G)$, and opening costs…

Data Structures and Algorithms · Computer Science 2019-04-25 Vincent Cohen-Addad , Marcin Pilipczuk , Michał Pilipczuk

Scheduling plays an important role in automated production. Its impact can be found in various fields such as the manufacturing industry, the service industry and the technology industry. A scheduling problem (NP-hard) is a task of finding…

Artificial Intelligence · Computer Science 2022-10-10 Hongjian Zhou , Boyang Gu , Chenghao Jin

In this paper we propose an extension of the Uncapacitated Hub Location Problem where the potential positions of the hubs are not fixed in advance. Instead, they are allowed to belong to a region around an initial discrete set of nodes. We…

Optimization and Control · Mathematics 2020-01-31 Víctor Blanco , Justo Puerto

Intermittent demand forecasting is a ubiquitous and challenging problem in production systems and supply chain management. In recent years, there has been a growing focus on developing forecasting approaches for intermittent demand from…

Applications · Statistics 2022-09-01 Li Li , Yanfei Kang , Fotios Petropoulos , Feng Li

State-of-the-art motion planners cannot scale to a large number of systems. Motion planning for multiple agents is an NP (non-deterministic polynomial-time) hard problem, so the computation time increases exponentially with each addition of…

In this paper we investigate a dynamic pricing model for constant demand elasticity where customers have a probability distribution on the number of items they order. This is a generalization from standard models which restrict customers to…

Optimization and Control · Mathematics 2018-03-01 Nyles Breecher , Richard Stockbridge

We introduce a problem that is a common generalization of the uncapacitated facility location and minimum latency (ML) problems, where facilities need to be opened to serve clients and also need to be sequentially activated before they can…

Data Structures and Algorithms · Computer Science 2010-09-14 Deeparnab Chakrabarty , Chaitanya Swamy

Reallocation scheduling is one of the most fundamental problems in various areas such as supply chain management, logistics, and transportation science. In this paper, we introduce the reallocation problem that models the scheduling in…

Data Structures and Algorithms · Computer Science 2021-11-05 Toshimasa Ishii , Jun Kawahara , Kazuhisa Makino , Hirotaka Ono

Federated and Continual Learning have emerged as potential paradigms for the robust and privacy-aware use of Deep Learning in dynamic environments. However, Client Drift and Catastrophic Forgetting are fundamental obstacles to guaranteeing…

Machine Learning · Computer Science 2023-09-06 Niklas Babendererde , Moritz Fuchs , Camila Gonzalez , Yuri Tolkach , Anirban Mukhopadhyay