Mathematical formulations and optimization algorithms for solving rich vehicle routing problems.

Objectives and methods of study: The main objective of this work is to analyze and solve three different rich selective Vehicle Routing Problems (VRPs). The first problem is a bi-objective variant of the well-known Traveling Purchaser Problem (TPP) in which the purchased products are delivered to customers. This variant aims to find a route for which the total cost (transportation plus purchasing costs) and the sum of the customers’s waiting time are simultaneously minimized. A mixed integer bi-objective programming formulation of the problem is presented and tested with CPLEX 12.6 within an ǫ-constraint framework which fails to find non-dominated solutions for instances containing more than 10 nodes. Therefore, a heuristic based on relinked local search and Variable Neighborhood Search (VNS) is proposed to approximate the Pareto front for large instances. The proposed heuristic was tested over a large set of artificial instances of the problem. Computational results over small-sized instances show that the heuristic is competitive with the ǫ-constraint method. Also, computational tests over large-sized instances were carried out in order to study how the characteristics of the instances impact the algorithm performance. The second problem consists of planning a selective delivery schedule of multiple products. The problem is modeled as a multi-product split delivery capacitated team orienteering problem with incomplete services, and soft time windows. The problem is modeled through a mixed integer linear programming formulation and approximated by means of a multi-start Adaptive Large Neighborhood Search (ALNS) metaheuristic. Computational results show that the multi-start metaheuristic reaches better results than its classical implementation in which a single solution is build and then improved. Finally, an Orienteering Problem (OP) with mandatory visits and conflicts, is formulated through five mixed integer linear programming models. The main difference among them lies in the way they handle the subtour elimination constraints. The models were tested over a large set of instances of the problem. Computational experiments reveal that the model which subtour elimination constraints are based on a single-commodity flow formulation allows CPLEX 12.6 to obtain the optimal solution for more instances than the other formulations within a given computation time limit. Contributions: The main contributions of this thesis are: • The introduction of the bi-objective TPP with deliveries since few bi-objective versions of the TPP have been studied in the literature. Furthermore, to the best of our knowledge, there is only one more work that takes into account deliveries in a TPP. • The design and implementation of a hybrid heuristic based on relinked local search and VNS to solve the bi-objective TPP with deliveries. Additionally, we provide guidelines for the application of the heuristic when different characteristics of the instances are observed. • The design and implementation of a multi-start adaptive large neighborhood search to solve a selective delivery schedule problem. • The experimental comparison among different formulations for an OP with mandatory nodes and conflicts

On the optimization of green multimodal transportation: A case study of the West German canal system

In this study, we address a biobjective multimodal routing problem that consists of selecting transportation modes and their respective quantities, optimizing transshipment locations, and allocating port orders. In the objective functions, we minimize total transportation costs and use the EcoTransit methodology to minimize total greenhouse gas emissions. The optimization model selects the transportation mode and transshipment port where quantities are transshipped from one mode to another. We compare inland waterway transportation and trucks encountering infrastructure failures that require rerouting or modal shifting in a real-life case study on the supply of goods for the chemical industry in the West German canal system. We propose a population-based heuristic to solve large instances in a reasonable computation time. A sensitivity analysis of demand, of varying lock times, and of infrastructure failure scenarios was conducted. We show that compared with inland waterway transportation, multimodal transportation reduces costs by 23% because of longer lock times. Our analysis shows that the use of inland waterway transportation only during infrastructure failures imposes nearly 28% higher costs per day depending on the failure location compared to that of the case of no failures. We also show that the use of a multimodal transportation system helps to reduce this cost increase in lock failure scenarios

Integrating operations research into green logistics:A review

Logistical activities have a significant global environmental impact, necessitating the adoption of green logistics practices to mitigate environmental effects. The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis. Operations research provides a means to balance environmental concerns and costs, thereby enhancing the management of logistical activities. This paper presents a comprehensive review of studies integrating operations research into green logistics. A systematic search was conducted in the Web of Science Core Collection database, covering papers published until June 3, 2023. Six keywords (green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation) were used to identify relevant papers. The reviewed studies were categorized into five main research directions: Green waste logistics, the impact of costs on green logistics, the green routing problem, green transport network design, and emerging challenges in green logistics. The review concludes by outlining suggestions for further research that combines green logistics and operations research, with particular emphasis on investigating the long-term effects of the pandemic on this field.</p

A tabu search-based heuristic for the dynamic oil distribution problem

Ce mémoire traite l'intégration dynamique des opérations de gestion des stocks et du transport avec la présence d'un évènement perturbateur, qui est la livraison urgente sur appel imprévue. En s'inspirant du cadre général de l'industrie énergétique et la distribution de l'huile à chauffage en particulier, après une revue de littérature exhaustive des problèmes de tournées de véhicules dynamiques et stockage-routage, nous introduisons une nouvelle variante qui cadre le problème dynamique de stockage-routage avec livraisons sur appel. Notre démarche de traitement s'est devisée en deux grandes étapes. Une première étape, statique et déterministe, s'est focalisée sur la description et la formulation mathématique du problème en se basant sur la programmation linéaire mixte et une résolution exacte à travers l'algorithme de branch-and-cut. Pour le besoin de l'intégration dynamique des livraisons incertaines sur appel dans un temps d'exécution raisonnable, une deuxième étape dynamique s'est concentrée sur le développement d'une heuristique basée sur la recherche tabou avec la configuration de deux politiques dynamiques de contrôle qui étudient les possibilités d'insérer les visites dynamiques soit dans la route en cours d'exécution ou dans celle de la période suivante dans le cas échéant. 72 instances ont été générées, et des analyses ont été menées sur différents facteurs qui peuvent influencer le taux de service des clients dynamiques aussi que les coûts d'opération.This thesis deals with the dynamic integration of inventory management and transportation operations with the uncertain event of unplanned deliveries following urgent calls. Inspired by the general framework of the energy industry and the distribution of heating oil, in particular, a comprehensive literature review of both problems of dynamic vehicle routing and inventory-routing are conducted. We then introduce a new variant, called the dynamic inventory-routing problem with customer requests. Our solution approach has been divided into two main steps. A static and deterministic first step focused on the mathematical description and formulation of the problem based on a mixed-integer programming model and the development of an exact solution approach through a branch and cut algorithm. Then, to dynamically integrate uncertain on-call deliveries in a reasonable execution time, a second dynamic step is established to develop a heuristic, based on tabu search, with the configuration of two dynamic control policies that consider the possibilities of inserting dynamic visits either in the route under the execution or in that of the following period. 72 instances are generated, and analyses are conducted on various factors that can influence the service level for dynamic customers and operation costs

Essays on Shipment Consolidation Scheduling and Decision Making in the Context of Flexible Demand

This dissertation contains three essays related to shipment consolidation scheduling and decision making in the presence of flexible demand. The first essay is presented in Section 1. This essay introduces a new mathematical model for shipment consolidation scheduling for a two-echelon supply chain. The problem addresses shipment coordination and consolidation decisions that are made by a manufacturer who provides inventory replenishments to multiple downstream distribution centers. Unlike previous studies, the consolidation activities in this problem are not restricted to specific policies such as aggregation of shipments at regular times or consolidating when a predetermined quantity has accumulated. Rather, we consider the construction of a detailed shipment consolidation schedule over a planning horizon. We develop a mixed-integer quadratic optimization model to identify the shipment consolidation schedule that minimizes total cost. A genetic algorithm is developed to handle large problem instances. The other two essays explore the concept of flexible demand. In Section 2, we introduce a new variant of the vehicle routing problem (VRP): the vehicle routing problem with flexible repeat visits (VRP-FRV). This problem considers a set of customers at certain locations with certain maximum inter-visit time requirements. However, they are flexible in their visit times. The VRP-FRV has several real-world applications. One scenario is that of caretakers who provide service to elderly people at home. Each caretaker is assigned a number of elderly people to visit one or more times per day. Elderly people differ in their requirements and the minimum frequency at which they need to be visited every day. The VRP-FRV can also be imagined as a police patrol routing problem where the customers are various locations in the city that require frequent observations. Such locations could include known high-crime areas, high-profile residences, and/or safe houses. We develop a math model to minimize the total number of vehicles needed to cover the customer demands and determine the optimal customer visit schedules and vehicle routes. A heuristic method is developed to handle large problem instances. In the third study, presented in Section 3, we consider a single-item cyclic coordinated order fulfillment problem with batch supplies and flexible demands. The system in this study consists of multiple suppliers who each deliver a single item to a central node from which multiple demanders are then replenished. Importantly, demand is flexible and is a control action that the decision maker applies to optimize the system. The objective is to minimize total system cost subject to several operational constraints. The decisions include the timing and sizes of batches delivered by the suppliers to the central node and the timing and amounts by which demanders are replenished. We develop an integer programing model, provide several theoretical insights related to the model, and solve the math model for different problem sizes

Risk-sensitive stochastic orienteering problems for trip optimization in urban environments

Orienteering Problems (OPs) are used to model many routing and trip planning problems. OPs are a variant of the well-known traveling salesman problem where the goal is to compute the highest reward path that includes a subset of vertices and has an overall travel time less than a specified deadline. However, the applicability of OPs is limited due to the assumption of deterministic and static travel times. To that end, Campbell et al. extended OPs to Stochastic OPs (SOPs) to represent uncertain travel times (Campbell et al. 2011). In this article, we make the following key contributions: (1) We extend SOPs to Dynamic SOPs (DSOPs), which allow for time-dependent travel times; (2) we introduce a new objective criterion for SOPs and DSOPs to represent a percentile measure of risk; (3) we provide non-linear optimization formulations along with their linear equivalents for solving the risk-sensitive SOPs and DSOPs; (4) we provide a local search mechanism for solving the risk-sensitive SOPs and DSOPs; and (5) we provide results on existing benchmark problems and a real-world theme park trip planning problem.</jats:p

Using Customer-related Data to Enhance E-grocery Home Delivery

International audiencePurpose: The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. This paper proposes an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.Design/methodology/approach: The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.Findings: Computational experiments reveal that the proposed approach could reduce the total travel distance by 3% to 20%, and theoretically increase the success rate of first-round delivery approximately by18%-26%.Research limitations/implications: The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.Practical implications: This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.Social implications: The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.Originality/value: Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper provides also a methodological approach to this line of research

The bi-objective travelling salesman problem with profits and its connection to computer networks.

This is an interdisciplinary work in Computer Science and Operational Research. As it is well known, these two very important research fields are strictly connected. Among other aspects, one of the main areas where this interplay is strongly evident is Networking. As far as most recent decades have seen a constant growing of every kind of network computer connections, the need for advanced algorithms that help in optimizing the network performances became extremely relevant. Classical Optimization-based approaches have been deeply studied and applied since long time. However, the technology evolution asks for more flexible and advanced algorithmic approaches to model increasingly complex network configurations. In this thesis we study an extension of the well known Traveling Salesman Problem (TSP): the Traveling Salesman Problem with Profits (TSPP). In this generalization, a profit is associated with each vertex and it is not necessary to visit all vertices. The goal is to determine a route through a subset of nodes that simultaneously minimizes the travel cost and maximizes the collected profit. The TSPP models the problem of sending a piece of information through a network where, in addition to the sending costs, it is also important to consider what “profit” this information can get during its routing. Because of its formulation, the right way to tackled the TSPP is by Multiobjective Optimization algorithms. Within this context, the aim of this work is to study new ways to solve the problem in both the exact and the approximated settings, giving all feasible instruments that can help to solve it, and to provide experimental insights into feasible networking instances

Desenvolvimento de uma heurística para a determinação de rotas de recolha e distribuição de produtos considerando múltiplos veículos

Trabalho de projecto de mestrado, Matemática Aplicada à Economia e Gestão, Universidade de Lisboa, Faculdade de Ciências, 2019Neste projeto, apresenta-se um problema de determinação de rotas de recolha e distribuição com escolha seletiva de mercados. Existe uma frota homogénea de veículos e existem pontos onde se faz a recolha de determinados produtos e, posteriormente, faz-se a distribuição pelos clientes, tendo estes uma dada procura que tem que ser satisfeita. Não é obrigatório visitar todos os pontos de recolha disponíveis. O objetivo é construir rotas para os veículos que partam de um depósito, passem por certos mercados para comprar os produtos, entreguem os produtos aos clientes e regressem ao depósito, de modo a minimizar a soma dos custos de aquisição dos produtos e dos custos de deslocação. Neste trabalho, faz-se uma breve referência a alguns problemas de determinação de rotas para veículos e à sua aplicação a casos reais. Apresenta-se, ainda, um modelo matemático em programação linear inteira mista. Desenvolve-se, para obter soluções admissíveis para este problema, uma heurística que é constituída por duas fases. A primeira fase consiste em criar rotas com um único cliente e com os mercados que o servem, tendo como base uma heurística desenvolvida para resolver o Travelling Purchaser Problem. Nesta primeira fase, constrói-se uma solução inicial, a qual é melhorada através de dois procedimentos: Market drop e Market exchange. A segunda fase consiste na fusão das rotas obtidas, juntando vários clientes na mesma rota, de modo a diminuir os custos de viagem. Os resultados computacionais são obtidos para dados gerados aleatoriamente, considerando duas áreas onde estão os clientes, o depósito e os mercados, dois tipos de probabilidade associados à existência de determinado produto em cada mercado e à probabilidade de a procura de determinado produto por parte de um cliente ser superior a zero e diferentes valores para número de mercados e procura. Fazse uma análise dos resultados obtidos em termos de média das melhorias percentuais quando se faz a fusão de rotas e em termos de tempos computacionais, considerando duas capacidades diferentes para os veículos.In this project, a pickup and delivery problem with selective choice of markets is presented. There is a fleet of homogenous vehicles which travels through pickup points to get certain products and then delivers them to the customers who have a certain demand that must be satisfied. It is not necessary to visit every available pickup point. The goal is to find a good, next to optimal, route for the vehicles that leave the depot, stop at certain markets where products are bought, deliver those products to the customers and then return to the depot, in order to minimize the sum of the purchasing costs and the travelling costs. In this project, a brief reference to some vehicle routing problems and some of its applications to the real world is made. A mixed integer linear programming model is presented. A heuristic is built to find feasible solutions for this problem. The heuristic consists of two phases, the first of which, consists of creating routes with a single customer and the markets which satisfy the customer’s demand. This phase is based on a heuristic for the Travelling Purchaser Problem where an initial feasible solution is found and improved upon through two procedures: Market Drop and Market Exchange. The second phase consists of merging the routes obtained beforehand, joining multiple customers in the same route, in order to decrease travelling costs. Some computational results were obtained for randomly generated data, considering two different areas for the depot, customers and markets, two different probabilities for the existence of a certain product in a certain market, two different probabilities for the existence of demand of a certain product for each customer and, lastly, different numbers of customers and markets. The results were analysed in regards to the average percentage improvements for the route merging, as well as regarding the computational time, considering two different maximum vehicle capacities

Managing Advanced Synchronization Aspects in Logistics Systems

In this thesis, we model various complex logistics problems and develop appropriate techniques to solve them. We improve industrial practices by introducing synchronized solutions to problems that were previously solved independently. The first part of this thesis focuses on cross-docks. We simultaneously optimize supplier orders and cross-docking operations to either reduce the storage space required or evenly distribute workload over the week. The second part of this thesis is devoted to transport problems in which two types of vehicles are synchronized, one of which can be transported by the other. The areas of application range from home services to parcel delivery to customers. After analyzing the complexity associated with these synchronized solutions (i.e., largescale problems for which the decisions depend on each other), we design algorithms based on the "destroy-and-repair" principle to find efficient solutions. We also introduce mathematical programs for all the considered problems. The problems under study arose directly from collaborations with various industrial partners. In this respect, our achieved solutions have been benchmarked with current industrial practice. Depending on the problem, we have been able to reduce the environmental impact generated by the industrial activities, the overall cost, or the social impact. The achieved gains compared to current industrial practice range from 10 to 70%, depending on the application. -- Dans cette thèse, nous modélisons divers problèmes logistiques complexes et développons des techniques appropriées pour les résoudre. Nous cherchons à améliorer certaines pratiques industrielles en introduisant des solutions synchronisées à des problèmes qui étaient auparavant résolus indépendamment. La première partie de cette thèse porte sur les cross-docks. Nous optimisons simultanément les commandes fournisseurs et les opérations au sein de la plateforme de logistique pour réduire l’espace de stockage requis ou répartir uniformément la charge de travail sur la semaine. La deuxième partie de cette thèse est consacrée aux problèmes de transport dans lesquels deux types de véhicules sont synchronisés, l’un pouvant être transporté par l’autre. Les domaines d’application vont du service à domicile à la livraison de colis chez des clients. Après avoir analysé la complexité des solutions synchronisées (c’est-à-dire des problèmes de grandes dimensions pour lesquels les décisions dépendent les unes des autres), nous concevons des algorithmes basés sur le principe de "destruction / reconstruction" pour trouver des solutions efficaces. Nous modélisons également les problèmes considérés avec la programmation mathématique. Les problèmes à l’étude viennent de collaborations avec divers partenaires industriels. A cet égard, les solutions que nous présentons sont comparées aux pratiques industrielles actuelles. En fonction du problème, nous avons pu réduire l’impact environnemental généré par les activités industrielles, le coût global, ou l’impact social des solutions. Les gains obtenus par rapport aux pratiques industrielles actuelles varient de 10 à 70%, selon l’application. Mot-clefs: Logistique, Synchronisation, Problème de transport, Tournée de véhicules, Plateforme de Cross-dock (transbordement), Programmation Mathématiques, Métaheuristiques, Matheuristiques, Instances Réelle