This thesis introduces a multi-objective variation of the personnel assignment problem, by including additional hierarchical and team constraints, which put restrictions on possible matchings of the bipartite graph. Besides maximization of summation of weights that are assigned to the edges of the graph, these additional constraints are also treated as objectives which are subject to minimization. In this work, different genetic algorithm approaches to multi-objective optimization are considered to solve the problem. Weighted Sum &ndash / a classical approach, VEGA - a non-elitist multi-objective evolutionary algorithm, and SPEA &ndash / a popular elitist multi-objective evolutionary algorithm, are considered as means of solution to the problem, and their performances are compared with respect to a number of multi-objective optimization criteria.

Ο γραμμικός προγραμματισμός είναι μια μεθοδολογία της Επιχειρησιακής Έρευνας η οποία ασχολείται με το πρόβλημα της κατανομής των περιορισμένων πόρων ενός συστήματος σε ανταγωνιζόμενες μεταξύ τους δραστηριότητες με τον καλύτερο δυνατό τρόπο. Από μαθηματικής σκοπιάς το πρόβλημα αφορά τη μεγιστοποίηση ή ελαχιστοποίηση μιας γραμμικής συνάρτησης σύμφωνα με κάποιους γραμμικούς περιορισμούς. Τόσο η μαθηματική διατύπωση του προβλήματος, όσο και μια συστηματική διαδικασία επίλυσής του, η μέθοδος Simplex, οφείλεται στον G.B. Duntzig στα 1947. Την ίδια εποχή ο J. Von Neuman διατύπωνε το αργότερα γνωστό ως δυϊκό πρόβλημα γραμμικού προγραμματισμού. Το πρώτο κεφάλαιο της παρούσης εργασίας ξεκινά με τη γενική μαθηματική θεώρηση των δύο προβλημάτων και συνεχίζει με τα βασικά θεωρήματα τα οποία αφορούν τη διαδικασία λύσης, τις ιδιότητές τους καθώς επίσης και τις σχέσεις που τα συνδέουν. Στο δεύτερο κεφάλαιο παρουσιάζονται διάφοροι τύποι ανάλυσης ευαισθησίας του γραμμικού μοντέλου, της μελέτης δηλαδή των αλλαγών που επιφέρουν στην άριστη λύση, αλλαγές σε διάφορα μεγέθη -παράμετροι- του προβλήματος. Στο ίδιο κεφάλαιο παρουσιάζεται η ανάλυση ευαισθησίας μιας ειδικής κλάσης προβλημάτων γραμμικού προγραμματισμού, του προβλήματος καταμερισμού εργασίας (εκχώρησης). Τέλος γίνεται μια σύντομη αναφορά στον υπολογισμό των δυϊκών τιμών στην περίπτωση των εκφυλισμένων λύσεων. / Linear programming is a method of Operations Research which deals with the problem of distribution of limited resources of a system to rivaling activities -with each other - in the best possible way. From mathematics point of view the problem concerns the maximization or minimization of a linear function according to certain linear restrictions. Not only the mathematic formulation of the problem, but also a systematic procedure of solution (gradualism), the Simplex method, are due to G. B. Duntzig (1947). At the same time J. Von Neuman formulated the later known as dual problem of linear programming. The first chapter of this paper starts with the general mathematical regard of these two problems and steps to the essential theorems used for the solution procedure, their attributes as well as the relations that bind them. In the second chapter various types of linear model’s sensitivity analysis are presented, the study of changes that lead to the most efficient solution, changes in various elements - parameters of the problem. At the same chapter the sensitivity analysis of special group of linear programming problems is presented, the assignment problem. Finally a brief note is made at the calculation of dual values in case of degenerated solutions.

Cette thèse propose un outil d’aide à la décision pour la gestion de processus de maintenance basée surune affectation optimale des ressources humaines afin d’améliorer la performance de la maintenance.En effet, une bonne performance de la fonction maintenance est indispensable pour maintenir laproductivité des installations industrielles, et donc de la compétitivité des entreprises manufacturières.L’approche que nous développons dans ce manuscrit procure un cadre de référence des leviersd’actions envisageables pour mesurer, évaluer, améliorer et optimiser la performance de lamaintenance. Nous prenons en considération un problème d’affectation des ressources humaines, quiprend en compte non seulement leurs disponibilités et compétences, mais aussi la gestion des urgencesd’intervention sur terrain.La méthode que nous proposons est basée sur un modèle de simulation à événements discrets,reproduisant au mieux un service de maintenance. Ceci nous a permis d’évaluer la situation via desindicateurs de performance présélectionnés. Pour optimiser le système, nous proposons un couplagedu modèle de simulation avec un module d’optimisation indépendant qui se réfère à une métaheuristiquebasée sur une approche Pareto. Notre proposition a été testée dans une entrepriseindustrielle réelle.L’approche que nous proposons donne un ensemble de solutions d’affectation des ressourceshumaines, aidant le décideur à mieux gérer l’indisponibilité de ses outils. Nous obtenons de bonsrésultats en un temps raisonnable. / In this thesis, a decision-making tool for maintenance management process based on assignment ofhuman resources is proposed in order to improve maintenance performance. An optimal maintenanceperformance is indispensable to guarantee the productivity and competitiveness of manufacturingcompanies.The proposed approach provides a framework of different possible levers to measure, evaluate,improve and optimize the maintenance performance. The assignment of human resources problem isconsidered. It takes into account different constraints like human resources availability, competences,urgency degree management of interventions requests etc.The proposed method is based on a discrete event simulation model, providing a better presentation ofthe maintenance service and better comprehensive thanks to the performance indicators. To improveuntil optimize the model, a simulation-based Pareto optimization method is introduced. Optimizationmodule was coded on independent programs in order to provide an opportunity of control thesimulation based optimization process.The proposed simulation based optimization method find good solutions in a reasonable amount oftime. Applying this technique on an industrial case-study, we show that it is more effective indetecting real faults than existing alternatives. The approach can be extended to cover other domainsand other types of simulation models.

A key challenge for manufacturing companies is to store parts in an efficient way atthe lowest cost possible. As the demand of differentiated products increases, togetherwith the fact that old products are not phased out at the same pace, the need of usingstorage space as dynamically as possible becomes vital.Scania’s engine assembly manufactures engines for various automotive vehicles andmarine & industry applications. The variation in engine range in Scania’s offeringleads to the need of holding a vast, and increasing, assortment of parts in the produc-tion. As a consequence, this puts more pressure on the logistics and furnishing withinthe engine assembly.This master thesis aims to facilitate the process of assigning parts’ storage locationsin the most profitable manner through an optimization model, the Location Model, inExcel VBA. Together with the model, suggestions of work methods are presented.By implementing the Location Model at Scania’s engine assembly, 4,98 % of all keptparts are recommended location changes, while resulting in cost savings, for the chosen30-day period. These location changes result in a cost saving of 6,73 % of the totallogistic costs for the same time period.

Cíle diplomové práce jsou popsat procesy probíhající v kontejnerovém přístavním terminálu, vytvořit přehled rozhodovacích problémů vznikajících v kontejnerovém přístavním terminálu z hlediska úrovně jejich typu řízení a plánování (strategické, taktické a operativní) a formulovat vybrané rozhodovací problémy a matematicky je analyzovat.

The diploma thesis focuses on tracing in layout by handlers between assembly lines in new plant for corporation Continental Automotive Czech Republic ltd, where boosters are produced. The theoretical part involves definitions of logistics, supply chain, material flow and handling equipment. Furthermore, methods of mathematic programming and software equipment are described, such as quadratic assignment problem, knapsack problem, travelling salesman problem from graph theory. In the practical part the situation in corporation has been analyzed and the data prepared for further examination. Then layout of plant and internal processes are evaluated and an appropriate model or concept of solution is selected. Subsequently, application in MS Excel is created with support of VBA scripts (3 kinds of layouts). The user manipulates with application followed by Solver for implementation of a new solution into practice. Finally, the models are interpreted and verified by Lingo. The focus of the thesis is the design of a layout change of a new plant including the description of tracing.

The less-than-truckload (LTL) transportation industry is highly competitive with low profit margins. Carriers in this industry strive to reduce costs and improve customer service to remain profitable. LTL carriers rely on a network of hubs and service centers to transfer freight. A hub is typically a cross docking terminal in which shipments from inbound trailers are unloaded and reassigned and consolidated onto outbound trailers going to the correct destinations. Freight handling in a hub is labor intensive, and workers must quickly transfer freight during a short time period to support customer service levels. Reducing shipment transfer time in hubs offers the opportunity to reduce labor costs, improve customer service, and increase competitive advantages for carriers. This research focuses on improving the efficiency of hub operations in order to decrease the handling costs and increase service levels for LTL carriers. Specifically, the following two decision problems are investigated: (1) assigning trailers to dock doors to minimize the total time required to transfer shipments from inbound trailers to destination trailers and (2) sequencing unloading and loading of freight to minimize the time required by dock employees. The trailer-to-door assignment problem is modeled as a Quadratic Assignment Problem (QAP). Both semi-permanent and dynamic layouts for the trailer-to-door assignment problem are evaluated. Improvement based heuristics, including pair-wise exchange, simulated annealing, and genetic algorithms, are explored to solve the trailer-to-door assignment problem. The freight sequencing problem is modeled as a Rural Postman Problem (RPP). A Balance and Connect Algorithm (BCA) and an Assign First and Route Second Algorithm (AFRSA) are investigated and compared to Balanced Trailer-at-a-Time (BTAAT), Balanced Trailer-at-a-Time with Offloading (BTAATWO), and Nearest Neighbor (NN). The heuristics are evaluated using data from two LTL carriers. For these data sets, both the total travel distance and the transfer time of hub operations are reduced using a dynamic layout with efficient freight sequencing approaches, such as the Balance and Connect Algorithm (BCA), the Balanced Trailer-at-a-Time with Offloading (BTAATWO), and the Nearest Neighbor (NN). Specifically, with a dynamic layout, the BCA reduces travel distance by 10% to 27% over BTAAT and reduces the transfer time by 17% to 68% over BTAAT. A simulation study is also conducted for hub operations in a dynamic and stochastic environment. The solutions from the door assignment and freight sequencing approaches are evaluated in a simulation model to determine their effectiveness in this environment. The simulation results further demonstrate that the performance measures of hub operations are improved using a dynamic layout and efficient freight sequencing approaches. The main contributions of this research are the integer programming models developed for the freight sequencing problem (FSP), based on the Rural Postman Problem (RPP). This is the first known application of the RPP for the FSP. Efficient heuristics are developed for the FSP for a single worker and for multiple workers. These heuristics are analyzed and compared to previous research using industry data. / Ph. D.

No description available.

Aujourd'hui, le problème de stationnement devient l'un des enjeux majeurs de la recherche dans la planification des transports urbains et la gestion du trafic. En fait, les conséquences de l'absence de places de stationnement ainsi que la gestion inadéquate de ces installations sont énormes. L'objectif de cette thèse est de fournir des algorithmes efficaces et robustes afin que les conducteurs gagnent du temps et de l'argent et aussi augmenter les revenus des gestionnaires de parking. Le problème est formulé comme un problème d'affectation multi-objectifs dans des environnements statique et dynamique. Tout d'abord, dans l'environnement statique, nous proposons de nouvelles heuristiques en deux phases pour calculer une approximation de l'ensemble des solutions efficaces pour un problème bi-objectif. Dans la première phase, nous générons l'ensemble des solutions supportées par un algorithme dichotomique standard. Dans la deuxième phase, nous proposons quatre métaheuristiques pour générer une approximation des solutions non supportées. Les approches proposées sont testées sur le problème du plus court chemin bi-objectif et le problème d'affectation bi-objectif. Dans le contexte de l'environnement dynamique, nous proposons une formulation du problème sous forme d'un programme linéaire en nombres entiers mixtes qui est résolue à plusieurs reprises sur un horizon de temps donné. Les fonctions objectives considérées, permettent un équilibre entre la satisfaction des conducteurs et l'intérêt du gestionnaire de parking. Deux approches sont proposées pour résoudre ce problème d'affectation dynamique avec ou sans phase d'apprentissage. Pour renforcer la phase d'apprentissage, un algorithme à estimation de distribution est proposé pour prévoir la demande future. Pour évaluer l'efficacité des algorithmes proposés, des essais de simulation ont été effectués. Aussi une mise en œuvre pilote a été menée dans le parking à l'Université de Valenciennes en utilisant une plateforme existante, appelée Context Aware Transportation Services (CATS), qui permet le déploiement dynamique de services. Cette plate-forme peut dynamiquement passer d'une approche à l'autre en fonction du contexte. Enfin cette thèse s'inscrit dans le projet SYstem For Smart Road Applications ( SYFRA). / The parking problem is nowadays one of the major issues in urban transportation planning and traffic management research. In fact, the consequences of the lack of parking slots along with the inadequate management of these facilities are tremendous. The aim of this thesis is to provide efficient and robust algorithms in order to save time and money for drivers and to increase the income of parking managers. The problem is formulated as a multi-objective assignment problem in static and dynamic environments. First, for the static environment, we propose new two-phase heuristics to calculate an approximation of the set of efficient solutions for a bi-objective problem. In the first phase, we generate the supported efficient set with a standard dichotomic algorithm. In the second phase we use four metaheuristics to generate an approximation of the non-supported efficient solutions. The proposed approaches are tested on the bi-objective shortest path problem and the biobjective assignment problem. For the dynamic environment, we propose a mixed integer linear programming formulation that is solved several times over a given horizon. The objective functions consist of a balance between the satisfaction of drivers and the interest of the parking managers. Two approaches are proposed for this dynamic assignment problem with or without learning phase. To reinforce the learning phase, an estimation of distribution algorithm is proposed to predict the future demand. In order to evaluate the effectiveness of the proposed algorithms, simulation tests have been carried out. A pilot implementation has also been conducted in the parking of the University of Valenciennes, using an existing platform called framework for context aware transportation services, which allows dynamic deployment of services. This platform can dynamically switch from one approach to another depending on the context. This thesis is part of the project SYstem For Smart Road Applications (SYFRA).

Made available in DSpace on 2016-08-10T10:40:17Z (GMT). No. of bitstreams: 1 Geovane Reges de Jesus Campos.pdf: 308868 bytes, checksum: 7d7dde587ca6eede4281609bfad2c151 (MD5) Previous issue date: 2012-09-04 / This paper presents a study for the classroom assignment problem for the PUC Goiás, Area 3, Campus I, based on a programming system (SAPA), the Hungarian algorithm, and on the idea of solving the problem time by time. The problem is solved with real data no more than 6 seconds. / Este trabalho apresenta um estudo para o problema de designação de salas de aula para a PUC Goiás, área 3, Campus I, baseado em um sistema de programação (SAPA), no algoritmo Húngaro e na idéia de resolver o problema horário por horário. O problema é resolvido, com dados reais, em não mais do que 6 segundos.