A study on exponential-size neighborhoods for the bin packing problem with conflicts

We propose an iterated local search based on several classes of local and large neighborhoods for the bin packing problem with conflicts. This problem, which combines the characteristics of both bin packing and vertex coloring, arises in various application contexts such as logistics and transportation, timetabling, and resource allocation for cloud computing. We introduce $O(1)$ evaluation procedures for classical local-search moves, polynomial variants of ejection chains and assignment neighborhoods, an adaptive set covering-based neighborhood, and finally a controlled use of 0-cost moves to further diversify the search. The overall method produces solutions of good quality on the classical benchmark instances and scales very well with an increase of problem size. Extensive computational experiments are conducted to measure the respective contribution of each proposed neighborhood. In particular, the 0-cost moves and the large neighborhood based on set covering contribute very significantly to the search. Several research perspectives are open in relation to possible hybridizations with other state-of-the-art mathematical programming heuristics for this problem.Comment: 26 pages, 8 figure

Multi-capacity combinatorial ordering GA in application to cloud resources allocation and efficient virtual machines consolidation

This paper describes a novel approach making use of genetic algorithms to find optimal solutions for multi-dimensional vector bin packing problems with the goal to improve cloud resource allocation and Virtual Machines (VMs) consolidation. Two algorithms, namely Combinatorial Ordering First-Fit Genetic Algorithm (COFFGA) and Combinatorial Ordering Next Fit Genetic Algorithm (CONFGA) have been developed for that and combined. The proposed hybrid algorithm targets to minimise the total number of running servers and resources wastage per server. The solutions obtained by the new algorithms are compared with latest solutions from literature. The results show that the proposed algorithm COFFGA outperforms other previous multi-dimension vector bin packing heuristics such as Permutation Pack (PP), First Fit (FF) and First Fit Decreasing (FFD) by 4%, 34%, and 39%, respectively. It also achieved better performance than the existing genetic algorithm for multi-capacity resources virtual machine consolidation (RGGA) in terms of performance and robustness. A thorough explanation for the improved performance of the newly proposed algorithm is given

Complexity of combinatorial ordering genetic algorithms COFFGA and CONFGA

This paper analyses the complexity of two Algorithms called COFFGA (Combinatorial Ordering First Fit Genetic Algorithm) and CONFGA (Combinatorial Ordering Next Fit Genetic Algorithm). It also identifies the parameters that affect the performance of these algorithms. The complexity of the GA depends on the problem being solved by this GA, as well as the operators of the GA itself. The complexity of COFFGA and CONFGA are analysed individually. Even of these algorithms are slightly different, they may have extremely different complexities depending on the differences in their fitness function or termination condition. To provide a provable bound on a problem, there must be a bound on the evaluation function as well as a manner by which the underlying problem is tied to the representation. Given that there is no standard complexity of the GA, and the complexity of any GA depends on the problem that being solved by this GA and its operators, then CONFGA and COFFGA are analysed with different complexities; although they built upon the same algorithm and they are used to solve the same problem (Cloud resource allocation problem), but they are different in their operators their fitness function and termination condition

Scalable User Assignment in Power Grids: A Data Driven Approach

The fast pace of global urbanization is drastically changing the population distributions over the world, which leads to significant changes in geographical population densities. Such changes in turn alter the underlying geographical power demand over time, and drive power substations to become over-supplied (demand ≪ capacity) or under-supplied (demand ≈ capacity). In this work, we make the first attempt to investigate the problem of power substation/user assignment by analyzing large scale power grid data. We develop a Scalable Power User Assignment (SPUA) framework, that takes large-scale spatial power user/substation distribution data and temporal user power consumption data as input, and assigns users to substations, in a manner that minimizes the maximum substation utilization among all substations. To evaluate the performance of SPUA framework, we conduct evaluations on real power consumption data and user/substation location data collected from Xinjiang Province in China for 35 days in 2015. The evaluation results demonstrate that our SPUA framework can achieve a 20%–65% reduction on the maximum substation utilization, and 2 to 3.7 times reduction on total transmission loss over other baseline methods

Material handling optimization in warehousing operations

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2018-2019.Les activités de distribution et d’entreposage sont des piliers importants de la chaîne d’approvisionnement. Ils assurent la stabilité du flux de matières et la synchronisation de toutes les parties prenantes du réseau. Un centre de distribution (CD) agit comme un point de découplage entre l’approvisionnement, la production et les ventes. La distribution comprend un large éventail d’activités visant à assurer la satisfaction de la demande. Ces activités passent de la réception au stockage des produits finis ou semi-finis, à la préparation des commandes et à la livraison. Les opérations d’un CD sont maintenant perçues comme des facteurs critiques d’amélioration. Elles sont responsables de la satisfaction d’un marché en évolution, exigeant des délais de livraison toujours plus rapides et plus fiables, des commandes exactes et des produits hautement personnalisés. C’est pourquoi la recherche en gestion des opérations met beaucoup d’efforts sur le problème de gestion des CDs. Depuis plusieurs années, nous avons connu de fortes avancées en matière d’entreposage et de préparation de commandes. L’activité de préparation de commandes est le processus consistant à récupérer les articles à leur emplacement de stockage afin d’assembler des commandes. Ce problème a souvent été résolu comme une variante du problème du voyageur de commerce, où l’opérateur se déplace à travers les allées de l’entrepôt. Cependant, les entrepôts modernes comportent de plus en plus de familles de produits ayant des caractéristiques très particulières rendant les méthodes conventionnelles moins adéquates. Le premier volet de cette thèse par articles présente deux importants et complexes problèmes de manutention des produits lors de la préparation des commandes. Le problème de préparation des commandes a été largement étudié dans la littérature au cours des dernières décennies. Notre recherche élargit le spectre de ce problème en incluant un ensemble de caractéristiques associées aux installations physiques de la zone de prélèvement, comme les allées étroites, et aux caractéristiques des produits (poids, volume, catégorie, fragilité, etc.). Une perspective plus appliquée à la réalité des opérations est utilisée dans notre développement d’algorithmes. Les déplacements liés à la préparation des commandes sont fortement influencés par le positionnement des produits. La position des produits dans la zone de prélèvement est déterminée par une stratégie d’affectation de stockage (storage assignment strategy). Beaucoup de ces stratégies utilisent de l’information sur les ventes des produits afin de faciliter l’accès aux plus populaires. Dans l’environnement concurrentiel d’aujourd’hui, la durée de vie rentable d’un produit peut être relativement courte. Des promotions peuvent également être faites pour pousser différents produits sur le marché. Le positionnement fourni par la stratégie d’hier ne sera probablement plus optimal aujourd’hui. Il existe plusieurs études mesurant l’impact d’une bonne réaffectation de produits sur les opérations de prélèvement. Cependant, ils étudient la différence des performances avec les positionnements passés et actuels. La littérature démontre clairement que cela apporte des avantages en termes d’efficacité. Toutefois, les déplacements nécessaires pour passer d’une position à une autre peuvent constituer une activité très exigeante. Ceci constitue le second volet de cette thèse qui présente des avancées intéressantes sur le problème de repositionnement des produits dans la zone de prélèvement. Nous présentons le problème de repositionnement des produits sous une forme encore peu étudiée aux meilleurs de nos connaissances : le problème de repositionnement. Plus précisément, nous étudions la charge de travail requise pour passer d’une configuration à l’autre. Cette thèse est structuré comme suit. L’introduction présente les caractéristiques et les missions d’un système de distribution. Le chapitre 1 fournit un survol de la littérature sur les principales fonctions d’un centre de distribution et met l’accent sur la préparation des commandes et les décisions qui affectent cette opération. Le chapitre 2 est consacré à l’étude d’un problème de préparation de commandes en allées étroites avec des équipements de manutention contraignants. Dans le chapitre 3, nous étudions un problème de préparation des commandes où les caractéristiques des produits limitent fortement les routes de prélèvement. Le chapitre 4 présente une variante du problème de repositionnement (reassignment) avec une formulation originale pour le résoudre. La conclusion suit et résume les principales contributions de cette thèse. Mots clés : Préparation des commandes, entreposage, problèmes de routage, algorithmes exacts et heuristiques, réaffectation des produits, manutention.Distribution and warehousing activities are important pillars to an effective supply chain. They ensure the regulation of the operational flow and the synchronization of all actors in the network. Hence, distribution centers (DCs) act as crossover points between the supply, the production and the demand. The distribution includes a wide range of activities to ensure the integrity of the demand satisfaction. These activities range from the reception and storage of finished or semi-finished products to the preparation of orders and delivery. Distribution has been long seen as an operation with no or low added value; this has changed, and nowadays it is perceived as one of the critical areas for improvement. These activities are responsible for the satisfaction of an evolving market, requiring ever faster and more reliable delivery times, exact orders and highly customized products. This leads to an increased research interest on operations management focused on warehousing. For several years, we have witnessed strong advances in warehousing and order picking operations. The order picking activity is the process of retrieving items within the storage locations for the purpose of fulfilling orders. This problem has long been solved as a variant of the travelling salesman problem, where the order picker moves through aisles. However, modern warehouses with more and more product families may have special characteristics that make conventional methods irrelevant or inefficient. The first part of this thesis presents two practical and challenging material handling problems for the order picking within DCs. Since there are many research axes in the field of warehousing operations, we concentrated our efforts on the order picking problem and the repositioning of the products within the picking area. The order picking problem has been intensively studied in the literature. Our research widens the spectrum of this problem by including a set of characteristics associated with the physical facilities of the picking area and characteristics of the product, such as its weight, volume, category, fragility, etc. This means that a more applied perspective on the reality of operations is used in our algorithms development. The order picking workload is strongly influenced by the positioning of the products. The position of products within the picking area is determined by a storage assignment strategy. Many of these strategies use product sales information in order to facilitate access to the most popular items. In today’s competitive environment, the profitable lifetime of a product can be relatively short. The positioning provided by yesterday’s assignment is likely not the optimal one in the near future. There are several studies measuring the impact of a good reassignment of products on the picking operations. However, they study the difference between the two states of systems on the picking time. It is clear that this brings benefits. However, moving from one position to another is a very workload demanding activity. This constitutes the second part of this thesis which presents interesting advances on the repositioning of products within the picking area. We introduce the repositioning problem as an innovative way of improving performance, in what we call the reassignment problem. More specifically, we study the workload required to move from one setup to the next. This thesis is structured as follows. The introduction presents the characteristics and missions of a distribution system. Chapter 1 presents an overview of the literature on the main functions of a DC and emphasizes on order picking and decisions affecting this operation. Chapter 2 is devoted to the study of a picking problem with narrow aisles facilities and binding material handling equipment. In Chapter 3, we study the picking problem with a set of product features that strongly constrain the picking sequence. Chapter 4 presents a variant of the reassignment problem with a strong and new formulation to solve it. The conclusion follows and summarizes the main contributions of this thesis. Key words: Order-picking, warehousing, routing problems, exact and heuristic algorithms, products reassignment, material handling

Road-based goods transportation : a survey of real-world logistics applications from 2000 to 2015

The vehicle routing problem has been widely studied from a technical point of view for more than 50 years. Many of its variants are rooted in practical settings. This paper provides a survey of the main real-life applications of road-based goods transportation over the past 15 years. It reviews papers in the areas of oil, gas and fuel transportation, retail, waste collection and management, mail and package delivery and food distribution. Some perspectives on future research and applications are discussed