A Comparison of Centralised and Decentralised Scheduling Methods Using a Simple Benchmark System

This paper is intended to provide a comparison of a centralised scheduling system, a simple Multi-Agent System (MAS), and a Mixed Integer Linear Programming (MILP) formulation. The systems are tested on a simulation of a small scale flexible job shop that has machines in series and in parallel. The performance of the systems is assessed by running a batch of randomized jobs and comparing the number of late jobs and the length of time by which they are delayed. Additionally, simulations with random product failure are included to assess how well the systems perform with disruptions

Heurística de programação da produção para uma indústria cerâmica

Mestrado em Engenharia e Gestão IndustrialAtualmente, uma organização industrial com vista a singrar no mercado global é fortemente influenciada por pressões que visam o aumento da eficiência global e consequente redução de custos operacionais. O desafio para as mesmas passa, portanto, por expurgar do produto tudo aquilo que não lhe acrescenta valor percetível pelo cliente e por maximizar a utilização dos vários recursos industriais instalados. No seguimento deste desafio, surge o Problema de Planeamento e Programação da Produção, ao qual é necessário dar uma resposta eficiente. Este projeto tem como objetivo estudar o problema da Programação da Produção numa indústria de pavimentos e revestimentos cerâmicos, desenvolvendo uma heurística construtiva capaz de traduzir com fiabilidade a realidade do processo produtivo da mesma e, se possível, auxiliar na sua resolução. O problema da programação da produção em estudo visa responder às questões: o quê, em que quantidade, quando e em que linha produzir, por forma a satisfazer as necessidades dos clientes num prazo previamente estipulado como admissível, garantindo o enchimento dos fornos ligados. Sem grandes constrangimentos ao normal lavor da Produção, pretende obter-se com a heurística planos de produção viáveis, que minimizem o tempo necessário para a conclusão do conjunto de referências com necessidades produtivas. O problema é também abordado através de um modelo exato como um problema de máquinas paralelas idênticas capacitado, com matriz de compatibilidades, setups de família e de subfamília e com lotes mínimos de produção. Quer a heurística quer o modelo de programação inteira mista desenvolvidos permitem obter planos de produção válidos, equivalentes aos obtidos atualmente pela empresa através dos meios de programação atuais, embora com um dispêndio de tempo muito inferior.Currently, an industrial organization in order to succeed in the global market is strongly influenced by pressures aimed at increasing the overall efficiency and reducing of their operating costs. The challenge for them is, therefore, to purge all that does not add discernible value to the product in perception of the customer and maximize utilization of the installed industrial resources. Following this challenge, there is the problem of Production Planning and Scheduling, which demands an effectively response. This project aims to study the problem of Production Scheduling in the flooring and ceramic tiles industry, developing a constructive heuristic able to reliably translate the reality of the production process and, if possible, assist in it's resolution. The problem of production scheduling in study aims to answer the questions: what, in what quantity, when and on which line to produce in order to meet customer needs within a previously stipulated acceptable time, ensuring the filling of connected furnaces. With no major constraints to the normal work flow, the heuristic aims to obtain viable production plans that minimize the production time required to complete the set of products needed. The problem is also addressed with an exact method as a problem of parallel identical capable machines, with compatibility matrix, with family and subfamily setups, and with minimum production batch sizes. Both the heuristic and the MIP model developed allows obtaining valid production plans, currently equivalent to those obtained currently by the company through the current programming means, although with a much lower time expenditure

Resolución de un problema real de asignación de personal a proyectos de auditoría

[ES] En este trabajo se aplican métodos de programación de la producción para modelizar y resolver un problema real de asignación y secuenciación de proyectos de auditoría al que se hace frente en el órgano de control interno del gobierno federal brasileño. En este problema, un gestor debe determinar, a partir de un conjunto predefinido de proyectos (obligatorios y optativos), el calendario laboral anual de cada uno de los auditores de su equipo, teniendo por objetivo maximizar la suma de beneficios asociados a la realización de los proyectos de naturaleza optativa. Los proyectos poseen restricciones de release times y deadlines, mientras los auditores presentan restricciones de indisponibilidades deterministas. Se propone un modelo de programación entera mixta (MIP) para la comprensión matemática del problema y también para intentar resolverlo óptimamente, pero no se encuentran soluciones óptimas exactas en un tiempo de computación razonable para los propósitos de la investigación. Solamente para las instancias pequeñas y medianas (hasta 10 auditores y 110 proyectos) aleatoriamente generadas para el problema se consigue obtener buenas soluciones factibles. Para las instancias de tamaño más grande, el modelo matemático solo es capaz de encontrar una cota superior relativa a la relajación lineal del problema. De este modo, se desarrollan dos algoritmos heurísticos constructivos con el lenguaje de programación Julia, los cuales logran encontrar, en un tiempo computacional muy pequeño, soluciones de alta calidad para el conjunto total de instancias probadas. Se hace una modificación en el segundo heurístico con el objetivo de incrementar su rendimiento y, al final, mediante un análisis de variancia (ANOVA), se verifica si las medias de los valores de las soluciones encontradas por cada uno de los heurísticos presentan diferencias estadísticamente significativas.[EN] In this work, production scheduling methods are applied to model and solve a real problem of audit projects assignment and scheduling, which is faced in the internal control body of the Brazilian federal government. In this problem, a manager must determine, from a predefined set of projects (required and optional ones), the annual work calendar of each auditor of his team, with the objective of maximizing the sum of benefits associated with the execution of the optional projects. There are restrictions of release times and deadlines concerning the projects, while auditors have restrictions related to deterministic unavailabilities. A mixed integer linear programming model (MIP) is proposed for the mathematical understanding of the problem and still for trying to solve it optimally, but no exact optimal solutions are found in a reasonable computational time for the purposes of the investigation. Only for small and medium-sized instances (up to 10 auditors and 110 projects) randomly generated for the problem, good feasible solutions can be obtained. For larger instances, the mathematical model is only able to find a best bound related to the linear relaxation of the problem. Then, two constructive heuristic algorithms are developed with Julia programming language, which succeed to find, in a very small computational time, high quality solutions for all randomly generated instances of the problem. A modification is introduced in the second heuristic with the aim of increase its performance and, finally, through a variance analysis (ANOVA), it is verified if the means of the solutions found by each heuristic differ amongst themselves in a statistically significant way.Teodoro Lima, R. (2019). Resolución de un problema real de asignación de personal a proyectos de auditoría. http://hdl.handle.net/10251/129497TFG

Three Essays on Data-Driven Optimization for Scheduling in Manufacturing and Healthcare

This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve this challenging scheduling problem of determining patient appointment times to minimize a weighted combination of patient wait and provider idle times for the team practice. To overcome the computational complexity associated with solving the problem under the large set of scenarios required to accurately capture uncertainty in this setting, our approach relies on a lower bounding technique based on solving an exhaustive and mutually exclusive group of scenario subsets. Our computational results identify the structure of optimal schedules and quantify the impact of nurse flexibility, patient crossovers and no-shows. We conclude with practical scheduling guidelines for team primary care practices. The third essay deals with another scheduling problem observed in a manufacturing setting similar to first essay, this time in aerospace industry. In Chapter 4, we propose mathematical models to optimize scheduling at a tactical and operational level in a job shop at an aerospace parts manufacturer and implement our methods using real-life data collected from this company. We generalize the Multi-Level Capacitated Lot-Sizing Problem (MLCLSP) from the literature and use novel computational techniques that depend on the data structure observed to reduce the size of the problem and solve realistically-sized instances in this chapter. We also provide a sensitivity analysis of different modeling techniques and objective functions using key performance indicators (KPIs) important for the manufacturer. Chapter 5 proposes extensions of models and techniques that are introduced in Chapters 2, 3 and 4 and outlines future research directions. Chapter 6 summarizes our findings and concludes the dissertation

Cross-dock door assignments: models, algorithms and extensions

In a cross-dock, goods coming from numerous origins get unloaded from incoming trucks, consolidated according to their destinations, and then loaded into outgoing trucks with little or no storage in between. We study a class of cross-dock door assignment problems where the assignments of origins (or incoming trucks) to inbound doors, and destinations (or outgoing trucks) to outbound doors are determined with the objective of minimizing the handling cost. Cross-dock door assignment problems are a fundamental class of optimization problems in cross-docking as they arise in more complex operational problems incorporating other decisions such as scheduling, routing, and workforce allocation. We first introduce several linear mixed integer programming formulations with Lagrangean relaxation and column generation algorithms based on some of these formulations. We then theoretically and computationally compare these formulations in terms of their linear, Lagrangean and combinatorial relaxations. Finally, we integrate the assignments with sequencing and selection decisions, based on our observations on a large cross-dock company in the USA, and introduce two new integer programming formulations. Where possible, our work is compared with existing ones, and new sets of instances are generated to either vary or enlarge the current data sets in the literature

Flexible Job-shop Scheduling Problem with Sequencing Flexibility: Mathematical Models and Solution Algorithms

Marketing strategists usually advocate increased product variety to attend better market demand. Furthermore, companies increasingly acquire more advanced manufacturing systems to take care of the increased product mix. Manufacturing resources with different capabilities give a competitive advantage to the industry. Proper management of the current productions resources is crucial for a thriving industry. Flexible job shop scheduling problem (FJSP) is an extension of the classical Job-shop scheduling problem (JSP) where operations can be performed by a set of candidate capable machines. An extended version of the FJSP, entitled FJSP with sequencing flexibility (FJSPS), is studied in this work. The extension considers precedence between the operations in the form of a directed acyclic graph instead of sequential order. In this work, a mixed integer programming (MILP) formulation is presented. A single objective formulation to minimize the weighted tardiness for the FJSP with sequencing flexibility is proposed. A different objective to minimize makespan is also considered. Due to the NP-hardness of the problem, a novel hybrid bacterial foraging optimization algorithm (HBFOA) is developed to tackle the FJSP with sequencing flexibility. It is inspired by the behaviour of the E. coli bacteria. It mimics the process to seek for food. The HBFOA is enhanced with simulated annealing (SA). The HBFOA has been packaged in the form of a decision support system (DSS). A case study of a small and medium-sized enterprise (SME) manufacturing industry is presented to validate the proposed HBFOA and MILP. Additional numerical experiments with instances provided by the literature are considered. The results demonstrate that the HBFOA outperformed the classical dispatching rules and the best integer solution of MILP when minimizing the weighted tardiness and offered comparable results for the makespan instances. In this dissertation, another critical aspect has been studied. In the industry, skilled workers usually are able to operate a specific set of machines. Hence, managers need to decide the best operation assignments to machines and workers. However, they need also to balance the workload between workers while accomplishing the due dates. In this research, a multi-objective mathematical model that minimizes makespan, maximal worker workload and weighted tardiness is developed. This model is entitled dual-resource FJSP with sequencing flexibility (DRFJSPS). It covers both the machine assignment and also the worker selection. Due to the intractability of the DRFJSPS, an elitist non-dominated sorting genetic algorithm (NSGA-II) is developed to solve this problem efficiently. The algorithm provides a set of Pareto-optimal solutions that the decision makers can use to evaluate the trade-offs of the conflicting objectives. New instances are introduced to demonstrate the applicability of the model and algorithm. A multi-random-start local search algorithm has been developed to assess the effectiveness of the adapted NSGA-II. The comparison of the solutions demonstrates that the modified NSGA-II provides a non-dominated efficient set in a reasonable time. Finally, a situation where there are multiple process plans available for a specific job is considered. This scenario is useful to be able to react to the current status of the shop where unpredictable circumstances (machine breakdown, current product mix, due dates, demand, etc.) can be accurately tackled. The determination of the process plan also depends on its cost. For that, a balance between cost, and the accomplishment of due dates is required. A multi-objective mathematical model that minimizes makespan, total processing cost and weighted tardiness are proposed to determine the sequence and the process plan to be used. This model is entitled flexible job-shop scheduling problem with sequencing and process plan flexibility (FJSP-2F). New instances are generated to show the applicability of the model

Ordonnancement des opérations dans une unité d'extrusion

Les travaux de ce mémoire traitent du problème d’ordonnancement et d’optimisation de la production dans un environnement de plusieurs machines en présence de contraintes sur les ressources matérielles dans une usine d’extrusion plastique. La minimisation de la somme pondérée des retards est le critère économique autour duquel s’articule cette étude car il représente un critère très important pour le respect des délais. Dans ce mémoire, nous proposons une approche exacte via une formulation mathématique capable des donner des solutions optimales et une approche heuristique qui repose sur deux méthodes de construction de solution sérielle et parallèle et un ensemble de méthodes de recherche dans le voisinage (recuit-simulé, recherche avec tabous, GRASP et algorithme génétique) avec cinq variantes de voisinages. Pour être en totale conformité avec la réalité de l’industrie du plastique, nous avons pris en considération certaines caractéristiques très fréquentes telles que les temps de changement d’outils sur les machines lorsqu’un ordre de fabrication succède à un autre sur une machine donnée. La disponibilité des extrudeuses et des matrices d’extrusion représente le goulot d’étranglement dans ce problème d’ordonnancement. Des séries d’expérimentations basées sur des problèmes tests ont été effectuées pour évaluer la qualité de la solution obtenue avec les différents algorithmes proposés. L’analyse des résultats a démontré que les méthodes de construction de solution ne sont pas suffisantes pour assurer de bons résultats et que les méthodes de recherche dans le voisinage donnent des solutions de très bonne qualité. Le choix du voisinage est important pour raffiner la qualité de la solution obtenue. Mots-clés : ordonnancement, optimisation, extrusion, formulation mathématique, heuristique, recuit-simulé, recherche avec tabous, GRASP, algorithme génétiqueThe thesis deals with the optimization of the production on a number of machines subject to limited availability of the resources in an extrusion facility. Because of its importance to meet deadlines, the objective is to minimize the sum of weighted tardiness. This work presents a linear formulation of the problem and a number of heuristic solution methods. The proposed heuristic solution methods can be divided into two main groups: construction methods and neighborhood search methods. Also solution construction methods are divided in two sub-groups: parallel construction heuristics and serial construction heuristics. Adaptations of the simulated annealing algorithm (SA), the genetic algorithm (GA), the Tabu search (TS) method and the Greedy randomized adaptive search procedure (GRASP) are developed. Five neighborhood structures are used within the four tested neighborhood search algorithms. In our problem, setup times are sequence dependent. Also, extruders and dies are the bottleneck piece of equipment in this industrial setting. Several problem instances were generated for the evaluation of heuristic scheduling algorithms. The experimental study shows that the construction heuristics are not sufficient to ensure good results, however the proposed neighborhood search methods perform very well. Also, the structure of neighborhoods plays an important role to guarantee better results. Keywords: scheduling, optimization, extrusion, mathematical formulation, heuristic, simulated-annealing, tabu-search, GRASP, genetic algorith

A study of current and possible future industrial engineering methodologies used to increase energy effieciency

Thesis (MScEng)--Stellenbosch University, 2012.ENGLISH ABSTRACT: Energy-related costs are increasing steadily. This is especially true in South Africa where we have been dealing with an energy crisis during the past couple of years. The increase in energy-related costs puts energy dependent industries under financial pressure. It is therefore imperative to find ways to improve the efficiency with which energy is being consumed in order to decrease the amount of money that has to be allocated to energy costs. The efficient consumption of energy at a facility is crucial and to increase that efficiency, Energy Management Programs (EMPs) should be implemented. An important component of EMPs is ascertaining the current energy consumption of a facility in order to identify areas where possible improvements can be made. This is done by completing an energy audit at the facility. After the energy audit has been completed and Energy Conservation Methods (ECMs) have been identified, the implementation of these methods should commence. The aim of this study is to determine how Industrial Engineering (IE) methods can play a more integral role in making South Africa more energy efficient. As part of this study, research was done to identify current EMCs being implemented in different areas and for different equipment in facilities. This information was compared to IE methods to identify the possible relationship between the ECMs and IE methods. Content analyses were completed on both IE and energy efficiency corpora using the Content Analysis Toolkit (CAT) program. These analyses identified important topics in these corpora and correlations between these topics in order to show correlations between the IE and energy efficiency fields. The most significant correlations identified, were between statistical methods and various energy efficiency topics. A case study was completed at a company in the Western Cape that manufactures electronic and integrated circuit products to implement the relevant ECMs. As part of the case study, an energy audit was completed at the facility. The implementation of a number of the ECMs has shown reductions in the daily kilowatt hours (kWh) consumptions. These reductions were obtained through the implementation of a Shut Down Management program, which highlights the importance of management in an energy conservation project. The application of optimisation algorithms for energy efficient design was examined through the optimisation of lighting design, using a Genetic Algorithm. It was found that a Genetic Algorithm is applicable to lighting design but requires further refinement in order to generate the most optimal design solutions.AFRIKAANSE OPSOMMING: Kostes verbonde aan energieverbruik is voortdurend besig om toe te neem.Dit is veral relevant in Suid-Afrika waar ons tans ’n energiekrisis beleef. Hierdie toename in energieverwante kostes plaas energie-afhanklike industrieë onder groot finansiële druk. Dit is daarom belangrik om maniere te vind om energieverbruik meer effektief te maak sodat die bedrag geld wat aan energieverwante kostes toegestaan word, verminder kan word. Effektiewe energieverbruik by ’n fasiliteit is kritiek en om hierdie effektiwiteit te verbeter behoort ’n energiebestuursprogram by die fasiliteit geïmplimenteer te word. ’n Belangrike komponent van energiebestuursprogramme is die bepaling van die huidige energieverbruik en dit word gebruik om die areas te identifiseer waar moontlike verbeteringe aangebring kan word. Die energieverbruik word bepaal deur ’n energie-oudit. Nadat die energie-oudit voltooi en die energiebesparingsmetodes bepaal is, moet hierdie metodes by die fasiliteit geïmplementeer word. Hierdie studie probeer vasstel hoe bedryfsingenieurswesemetodes ‘n groter rol kan speel in die proses om Suid-Afrika meer energie-effektief te maak. Navorsing is gedoen oor energiebesparingsmetodes wat in verskillende areas en vir verskillende toerusting in fasiliteite geïmplementeer word. Hierdie inligting is daarna vergelyk met bedryfsingenieurswesemetodes om juis die moontlike verhouding tussen hierdie twee tipe metodes te identifiseer. Analises was gedoen in bedryfsingenieurswese en energie-effektiwiteitskorpusse met die gebruik van die ‘Content Analysis Toolkit’ program. Belangrike onderwerpe en verwantskappe tussen hierdie onderwerpe in die korpusse is identifiseer om sodoende korrelasies tussen die bedryfsingenieurswese- en energie-effektiwiteitsveld uit te lig. Die mees betekenisvolle korrelasies was tussen statistiese metodes en verskeie energieeffektiwiteitsonderwerpe identifiseer. ’n Gevallestudie is by ’n maatskappy in die Wes-Kaap wat geïntegreerde elektroniese stroombane vervaardig gedoen, om die relevante energiebesparingsmetodes te implementeer. ’n Energie-oudit is as deel van die gevallestudie by die fasiliteit gedoen. Die aantal energiebesparingsmetodes wat wel geïmplementeer is, het ’n verlaging in die kilowatture (kWh) teweeggebring. Hierdie verlagings is verkry deur die implementering van ’n afskakelingsbestuursprogram wat die belangrikheid van bestuur in ’n energiebesparingsprogram uitlig. Die toepaslikheid van optimiseringsalgoritmes vir energie-effektiewe ontwerp is getoets deur die optimisering van ’n liguitlegontwerp met behulp van ’n genetiese algoritme. Daar is gevind dat ’n genetiese algoritme wel toegepas kan word, maar dat dit verbeteringe benodig

Multikriterielle Ablaufplanung und -steuerung in dynamischen und stochastischen Umgebungen : Ein Beitrag zur Erstellung robuster Ablaufpläne für die Frachtabfertigung in Luftfrachtterminals

Luftfrachtterminals stellen die zentrale Schnittstelle für den Umschlag von Fracht in der Luftfrachttransportkette dar. Ein stetiges Wachstum des globalen Luftfrachtbedarfs in Kombination mit steigenden Sicherheitsanforderungen stellt die Frachtabfertigung innerhalb der kapazitativ beschränkten Terminals vor neue Herausforderungen. Eine effiziente Ablaufplanung und -steuerung der Frachtabfertigungsaufträge ist daher essenziell, um die Fracht mit der für den Kunden gewohnten Servicequalität zu bearbeiten. In der vorliegenden Arbeit wird ein Ablaufplanungs- und -steuerungssystem in Form einer Architektur umgesetzt, das eine proaktiv-reaktive Ablaufplanung ermöglicht und dabei die dynamische und stochastische Systemumgebung berücksichtigt. Die rollierende proaktive Ablaufplanung stellt das zentrale Element der Architektur dar. Diese dient der Erstellung robuster Ablaufpläne, die eine Immunisierung gegenüber stochastischen Bearbeitungszeiten der Frachtabfertigungsaufträge gewährleisten. Grundlage für die Quantifizierung der Bearbeitungszeitunsicherheiten neuer Aufträge stellen Informationen über historische Abfertigungsaufträge dar, aus denen ein Informationsstand abgeleitet wird. Dieses Vorgehen gewährleistet die kontinuierliche Adaption der Ablaufplanung an sich ändernde Prozessunsicherheiten bei der Bearbeitung von Fracht. Ergänzend werden reaktive Maßnahmen im Rahmen der Ablaufsteuerung aufgezeigt, die eine ereignisorientierte Revision des aktiven Ablaufplans ermöglichen. Die erstellte Architektur wird anhand realer und synthetischer Testinstanzen validiert. Die Validierungsergebnisse zeigen, dass der vorgestellte Ansatz ein effektives Konzept darstellt, um die Robustheit erstellter Ablaufpläne zu erhöhen und die Ablaufplanung automatisiert an bestehende Prozessunsicherheiten anzupassen.Air cargo terminals represent the major interface in the air freight transport chain for the transshipment of freight. A continuous growth of the global demand for air freight combined with increased safety requirements pose new challenges to the freight handling within the capacity restricted terminals. Therefore, an efficient scheduling and control of the freight handling jobs is essential for handling the freight with the service quality the customer is used to. In the present work a scheduling and control system in the form of an architecture is developed that enables a proactive-reactive scheduling considering the dynamic and stochastic system environment. The rolling proactive scheduling represents the central element of the architecture. It is used to create robust schedules, which ensure the immunization against stochastic processing times of the freight handling jobs. The basis to quantify the processing time uncertainties of new jobs are information about historical freight handling jobs, from which an information base is derived. This approach ensures the continuous adaptation of the scheduling system to changing process uncertainties of the freight handling jobs. Additionally, reactive methods for the sequence control are illustrated that enable an event-oriented revision of the active schedule. The developed architecture is validated on real and synthetic test instances. The validation results show the effectiveness of the presented approach to increase the robustness of created schedules and to automatically adapt the scheduling process to existing process uncertainties.von Simon Boxnick, M. Sc. ; Dekanin: Prof. Dr. Caren Sureth-Sloane, Referent: Prof. Dr.-Ing. habil. Wilhelm Dangelmaier, Korreferentin: Prof. Dr. Leena SuhlTag der Verteidigung: 10.05.2016Universität Paderborn, Fakultät für Wirtschaftswissenschaften, Univ., Dissertation, 201