This research is concerned with the development of efficient solutions to various problems that arise in the flow-shop environments which utilize lot-streaming. Lot streaming is a commonly used process of splitting production lots into sublots and, then, of scheduling the sublots in an overlapping fashion on the machines, so as to expedite the progress of orders in production and to improve the overall performance of the production system. The different lot-streaming problems that arise in various flow-shop environments have been divided into two categories, single-lot problems and multiple-lot problems. Further classification of the multiple-lot problems into the lot streaming sequencing problem (LSSP) and the flow-shop lot-streaming (FSLS) problem is made in this work. This classification is motivated by the occurrence of these problems in the industry. Several variants of these problems are addressed in this research. In agreement with numerous practical applications, we assume sublots of equal sizes. It turns out that this restriction paves the way to the relaxation of several typical limitations of current lot-streaming models, such as assumption of negligible transfer and setup times or consideration of only the makespan criterion. For the single-lot problem, a goal programming (GP) approach is utilized to solve the problem for a unified cost objective function comprising of the makespan, the mean flow time, the average work-in-process (WIP), and the setup and handling related costs. A very fast optimal solution algorithm is proposed for finding the optimal number of sublots (and, consequently, the sublot size) for this unified cost objective function in a general m-machine flow shop. For the more complicated multiple-lot problem, a near-optimal heuristic for the solution of the LSSP is developed. This proposed heuristic procedure, referred to as the Bottleneck Minimal Idleness (BMI) heuristic, identifies and employs certain properties of the problem that are irregular in traditional flow-shop problems, particularly the fact that the sublot sizes eminating from the same lot type and their processing times (on the same machines) are identical. The BMI heuristic attempts to maximize the time buffer prior to the bottleneck machine, thereby minimizing potential bottleneck idleness, while also looking-ahead to sequence the lots with large remaining process time earlier in the schedule. A detailed experimental study is performed to show that the BMI heuristic outperforms the Fast Insertion Heuristic (the best known heuristic for flow-shop scheduling), when modified for Lot Streaming (FIHLS) and applied to the problem on hand. For the FSLS problem, several algorithms are developed. For the two-machine FSLS problem with an identical sublot-size for all the lots, an optimal pseudo-polynomial solution algorithm is proposed. For all practical purposes (i.e., even for very large lot sizes), this algorithm is very fast. For the case in which the sublot-sizes are lot-based, optimal and heuristic procedures are developed. The heuristic procedure is developed to reduce the complexity of the optimal solution algorithm. It consists of a construction phase and an improvement phase. In the construction phase, it attempts to find a near-optimal sequence for the lots and then, in the improvement phase, given the sequence, it attempts to optimize the lot-based sublot-sizes of each of the lots. Extensions of the solution procedures are proposed for the general m-machine FSLS problem. A comprehensive simulation study of a flow shop system under lot streaming is conducted to support the validity of the results and to demonstrate the effectiveness of the heuristic procedures. This study clearly indicates that, even in dynamic practical situations, the BMI rule, which is based on the proposed BMI heuristic, outperforms existing WIP rules, commonly used in industry, in scheduling a flow-shop that utilizes lot streaming. With respect to the primary performance measure - cycle time (or MFT) - the BMI rule demonstrates a clear improvement over other WIP rules. It is further shown that it also outperforms other WIP rules with respect to the output variability measure, another important measure in flow-shop systems. The effects of several other factors, namely system randomness, system loading, and bottleneck-related (location and number), in a flow-shop under lot streaming, are also reported. / Ph. D.

In der vorliegenden Arbeit wird ein Fragebogen zur Evaluation der Gebrauchstauglichkeit von Online-Shops entwickelt und Hinweise auf seine Reliabilität und Validität erbracht. Damit leistet die Arbeit einen Beitrag zur Verbesserung der Gebrauchstauglichkeit von Online-Shops zum Vorteil von Kunden und Anbietern. Gebrauchstauglichkeit ist ein komplexes Konstrukt, das sich vor allem durch seine Abhängigkeit von Produkt- und Benutzereigenschaften sowie von Eigenschaften des Nutzungskontexts und den Nutzungszielen der Benutzer auszeichnet. Eine Evaluation der Gebrauchstauglichkeit eines Online-Shops kann somit grundsätzlich nicht sinnvoll erfolgen. Vielmehr müssen bei der Evaluation die genannten Randbedingungen der Benutzung berücksichtigt werden. Zur Evaluation der Gebrauchstauglichkeit stehen verschiedene Methoden zur Verfügung. Sie lassen sich danach unterscheiden, ob sie prädiktiv oder deskriptiv, verhaltensbasiert oder meinungsbasiert sind und ob ihnen objektive oder subjektive Kriterien zugrunde liegen. Daraus ergeben sich für die verschiedenen Methoden unterschiedliche Anwendungsszenarien. Die Fragebogenmethode wird als geeignete Evaluationsmethode identifiziert, weil sie eine subjektive, benutzerbasierte Messung der Gebrauchstauglichkeit erlaubt, was bei der Evaluation speziell von Online-Shops, deren Benutzung in der Regel freiwillig erfolgt, zu aussagekräftigen Ergebnissen führt. Nach der aufwendigen und sorgfältigen Entwicklung des Fragebogens wird dieser auf seine Validität hin überprüft. Dabei wird eine weitgehende Gültigkeit des Fragebogens festgestellt. So stimmt die durch eine benutzerzentrierte Evaluation dreier Online-Shops mit dem Fragebogen erzeugte Rangreihe weitgehend mit der überein, die sich aus einem Expertenrating ergibt. Außerdem ist der Fragebogen sensitiv für Unterschiede zwischen Online-Shops, die sich hinsichtlich ihrer ergonomischen Gestaltung bezüglich einer spezifischen Kaufphase (Produktsuche) unterscheiden.

In this work, we investigate job-shop problems where limited capacity buffers to store jobs in non-processing periods are present. In such a problem setting, after finishing processing on a machine, a job either directly has to be processed on the following machine or it has to be stored in a prespecified buffer. If the buffer is completely occupied the job may wait on its current machine but blocks this machine for other jobs. Besides a general buffer model,also specific configurations are considered.The key issue to develop fast heuristics for the job-shop problem with buffers is to find a compact representation of solutions. In contrast to the classical job-shop problem,where a solution may be given by the sequences of the jobs on the machines, now also the buffers have to be incorporated in the solution representation. In this work, we propose two solution representations for the job-shop problem with buffers. Furthermore, we investigate whether the given solution representations can be simplified for specific buffer configurations. For the general buffer configuration it is shown that an incorporation of the buffers in the solution representation is necessary, whereas for specific buffer configurations possible simplifications are presented. Based on the given solution representations we develop local search heuristics in the second part of this work. Therefore, the well-known block approach for the classical job-shop problem is generalized to the job-shop problem with specific buffer configurations.

The priorities of executing the manufacturing orders generated by an MRP system are often in operational conflicts with the dynamics of the manufacturing floor. It is not uncommon for a given manufacturing order to reach the shop floor several weeks or longer after being "opened" by an MRP system where it may face a chaotic case of large queues, machine down-time, parts shortage, scrap problems and other resource management constraints. Many companies have resorted to the Manufacturing Execution System (MES) software solution to resolve these problems. This method first gained popularity in mid-90’s within the semiconductor industry. An MES approach is an on-line, real-time data gathering, analysis and storage to assist in short-interval scheduling (shift or day) manufacturing operations with an emphasis on revising scheduling priorities. It is essentially an information system tool for the shop floor and if designed properly, it may be used as an advisory system for effective decision-making. However, in implementation MES faces several challenges including the proper software platform/architecture, integration within ERP or a stand-alone best-of-breed, amount and type of data/information to be exchanged with the MRP engine, and a user-centered interface for various layers of decision making. This paper will provide a detailed background on various technical, software, and organizational factors that the use of an MES implementation may impose upon the practitioner. Furthermore, and as a case study, it will discuss a systematic implementation strategy for MES at a high-tech company in California. The discussion of the critical success factors in implementation planning will hopefully be of value to both practitioners and researchers in similar projects.

In today’s society, it is increasingly important for retailers to have an online presence, yet the adoption rate of e-commerce by small retailers is still lagging behind the that of larger retailers. This is due to the difficulty small retailers have to overcome the barriers to develop their web-shops, such as cost and time. This thesis will examine the barriers of single-store independent retail businesses to sell and market their goods online. It will use the Technology Acceptance Model framework developed by Davis (1986) to help understand how the barriers affect the retailers attitude towards the process of developing their web-shops. Specifically, it will ask the retailers, through interviews, what barriers exist, what their perception of difficulty to overcome these barriers is, and what their perception of importance to overcome these barriers is. The major findings show that the barriers for retailers have not changed in the past decade, nor has the difficulty level of overcoming these barriers. The majority of small retailers who have not yet developed their web-shops don’t feel that the effort to do so is worth the potential gains, yet the small retailers who have already developed their web-shops did feel it was worth the effort. The retailers all felt that the process was more difficult than it should be, and insisted they would make the leap if the cost and effort required was reduced.

No description available.

No description available.

As the Army transitions to the Army Force Generation (ARFORGEN) deployment cycle, it must adjust its many operations in support of ARFORGEN. Specifically, the Initial Military Training (IMT) must be able to adjust the scheduling of its classes for newly enlisted service members to finish training such that they fulfill Brigade Combat Team (BCT) requirements within their common due windows. We formulate this problem as a lot streaming problem. Lot streaming splits a batch of jobs into sublots,which are then processed over the machines in an overlapping fashion. To schedule classes for the IMT, there are two stages that must be coordinated: Basic Training (BT) and Advanced Individual Training (AIT). For the Army Force Generation problem, the classes are considered as sublots that are streamed from one stage to the next. For this process, the model formulation must address determination of class sizes and scheduling of soldiers and classes at the two stages such that (1) the start times of the soldiers at Stage 2 are greater than their completion times at Stage 1, and (2) the assignment of requisite number of soldiers is made to each BCT, so as to minimize the total flow time. We propose a decomposition-based approach for the solution of this problem. In an effort to decompose the problem, the original lot streaming problem is reformulated such that the master problem selects an optimal combination of schedules for training classes and assigning soldiers to BCTs. A complete schedule selected in the master problem includes the assignments of soldiers to classes in BT, AIT, and their assignments to the BCTs, so as to minimize the total flow time as well as earliness and tardiness for regular Army units. Earliness and Tardiness are defined as the length of the time a soldier waits before and after the due date, respectively, of the BCT to which he or she is assigned. Our decomposition-based method enables solution of larger problem instances without running out of memory, and it affords CPU time reductions when compared with the CPU times required for these problem instances obtained via direct application of CPLEX 12.1. Our investigation into the structure of the problem has enabled further improvement of the proposed decomposition-based method. This improvement is achieved because of a result, which we show, that the first and second-stage scheduling problems need not be solved as one combined subproblem, but rather, they can be solved sequentially, the first stage problem followed by the second stage problem. The combination of Stage 1 and Stage 2 problems as one subproblem creates several additional enumerations of possible schedules the model must generate. By reducing this number of enumerations, the computational effort involved in solving the model reduces significantly, thereby allowing reductions in CPU time. In the Sequential approach, the completion times of soldiers determined at Stage 1 are passed to Stage 2 as bounds on their completion times at Stage 2. We prove that solving the combined subproblem sequentially as two subproblems is optimal when the first stage has no limit on the batch size and the ready times of the soldiers at Stage 1 are the same. For the Army Force Generation problem, we use unequal ready times, and therefore, solving the scheduling problems for the first two stages as sequential subproblems can lead to suboptimal solutions. Our experimental investigation shows efficacy of solving larger-sized problem instances with this method. We also recommend various potential additions to improve the Sequential approach for application to the overall Army problem. We have also demonstrated the use of our methodology to a real-life problem instance. Our methodology results in schedules for IMT with an estimated 28% reduction in mean flow time for soldiers over what is currently experienced in practice. We apply this Sequential approach to various extensions of the problem on hand that pertain to hybrid flow shop and agile manufacturing environments. Results of our computational investigation show the effectiveness of using the Sequential approach over direct solution by CPLEX from the viewpoint of both optimality gap and the CPU time required. In particular, we consider two different model configurations for a hybrid flow shop and three different model configurations for an agile manufacturing facility. / Ph. D.

[ES] En esta Tesis Doctoral se aborda el problema del taller de flujo de permutación considerando recursos adicionales renovables, que es una versión más realista del clásico problema de taller de flujo de permutación, muy estudiado en la literatura. La inclusión de los recursos ayuda a acercar el mundo académico-científico al mundo real de la industria. Se ha realizado una completa revisión bibliográfica que no se ha limitado a problemas del taller de flujo, sino que han revisado problemas similares del ámbito de scheduling que consideren recursos. En esta revisión, no se han encontrado en la literatura artículos para el problema concreto que se estudia en esta tesis. Por ello, la aportación principal de esta Tesis Doctoral es el estudio por primera vez de este problema y la propuesta y adaptación de métodos para su resolución. Inicialmente, el problema se modeliza a través de un modelo de programación lineal entera mixta (MILP). Dada la complejidad del problema, el MILP es capaz de resolver instancias de un tamaño muy pequeño. Por ello, es necesario adaptar, diseñar e implementar heurísticas constructivas y metaheurísticas para obtener buenas soluciones en un tiempo de computación razonable. Para evaluar la eficacia y eficiencia de los métodos propuestos, se generan instancias de problemas partiendo de los conjuntos más utilizados en la literatura para el taller de flujo de permutación. Se utilizan estas instancias propuestas tanto para calibrar los distintos métodos como para evaluar su rendimiento a través de experimentos computacionales masivos. Los experimentos muestran que las heurísticas propuestas son métodos sencillos que consiguen soluciones factibles de una forma muy rápida. Para mejorar las soluciones obtenidas con las heurísticas y facilitar el movimiento a otros espacios de soluciones, se proponen tres metaheurísticas: un método basado en búsqueda local iterativa (ILS), un método voraz iterativo (IG) y un algoritmo genético con búsqueda local (HGA). Todos ellos utilizan las heurísticas propuestas más eficaces como solución o soluciones iniciales. Las metaheurísticas obtienen las mejores soluciones utilizando tiempos de computación razonables, incluso para las instancias de mayor tamaño. Todos los métodos han sido implementados dentro de la plataforma FACOP (Framework for Applied Combinatorial Optimization Problems). Dicha plataforma es capaz de incorporar nuevos algoritmos de optimización para problemas de investigación operativa relacionados con la toma de decisiones de las organizaciones y está diseñada para abordar casos reales en empresas. El incorporar en esta plataforma todas las metodologías propuestas en esta Tesis Doctoral, acerca el mundo académico al mundo empresarial. / [CA] En aquesta Tesi Doctoral s'aborda el problema del taller de flux de permutació considerant recursos addicionals renovables, que és una versió més realista del clàssic problema de taller de flux de permutació, molt estudiat a la literatura. La inclusió dels recursos ajuda a apropar el món acadèmic-científic al món real de la indústria. S'ha realitzat una revisió bibliogràfica completa que no s'ha limitat a problemes del taller de flux, sinó que ha revisat problemes similars de l'àmbit de scheduling que considerin recursos. En aquesta revisió, no s'ha trobat a la literatura articles per al problema concret que s'estudia en aquesta tesi. Per això, l'aportació principal d'aquesta Tesi Doctoral és l'estudi per primera vegada d'aquest problema i la proposta i l'adaptació de mètodes per resoldre'ls. Inicialment, el problema es modelitza mitjançant un model de programació lineal sencera mixta (MILP). Donada la complexitat del problema, el MILP és capaç de resoldre instàncies d'un tamany molt petita. Per això, cal adaptar, dissenyar i implementar heurístiques constructives i metaheurístiques per obtenir bones solucions en un temps de computació raonable. Per avaluar l'eficàcia i l'eficiència dels mètodes proposats, es generen instàncies de problemes partint dels conjunts més utilitzats a la literatura per al taller de flux de permutació. S'utilitzen aquestes instàncies proposades tant per calibrar els diferents mètodes com per avaluar-ne el rendiment a través d'experiments computacionals massius. Els experiments mostren que les heurístiques proposades són mètodes senzills que aconsegueixen solucions factibles de manera molt ràpida. Per millorar les solucions obtingudes amb les heurístiques i facilitar el moviment a altres espais de solucions, es proposen tres metaheurístiques: un mètode basat en cerca local iterativa (ILS), un mètode voraç iteratiu (IG) i un algorisme genètic híbrid (HGA). Tots ells utilitzen les heurístiques proposades més eficaces com a solució o solucions inicials. Les metaheurístiques obtenen les millors solucions utilitzant temps de computació raonables, fins i tot per a les instàncies més grans. Tots els mètodes han estat implementats dins de la plataforma FACOP (Framework for Applied Combinatorial Optimization Problems). Aquesta plataforma és capaç d'incorporar nous algorismes d'optimització per a problemes de recerca operativa relacionats amb la presa de decisions de les organitzacions i està dissenyada per abordar casos reals a empreses. El fet d'incorporar en aquesta plataforma totes les metodologies proposades en aquesta Tesi Doctoral, apropa el món acadèmic al món empresarial. / [EN] In this Doctoral Thesis, the permutation flowshop problem is addressed considering additional renewable resources, which is a more realistic version of the classic permutation flowshop problem, widely studied in the literature. The inclusion of resources helps to bring the academic-scientific world closer to the real world of industry. A complete bibliographic review has been carried out that has not been limited to flow shop problems, but has reviewed similar problems in the scheduling field that consider resources. In this review, no articles have been found in the literature for the specific problem studied in this thesis. Therefore, the main contribution of this Doctoral Thesis is the study for the first time of this problem and the proposal and adaptation of methods for its resolution. Initially, the problem is modeled through a mixed integer linear programming (MILP) model. Given the complexity of the problem, the MILP is capable of solving very small instances. Therefore, it is necessary to adapt, design and implement constructive heuristics and metaheuristics to obtain good solutions in a reasonable computation time. In order to evaluate the effectiveness and efficiency of the proposed methods, problem instances are generated starting from the sets most used in the literature for the permutation flowshop. These proposed instances are used both to calibrate the different methods and to evaluate their performance through massive computational experiments. Experiments show that proposed heuristics are simple methods that achieve feasible solutions very quickly. To improve the solutions obtained with the heuristics and facilitate movement to other solution spaces, three metaheuristics are proposed: a method based on iterated local search (ILS), an iterative greedy method (IG) and a hybrid genetic algorithm (HGA). All of them use the most effective proposed heuristics as initial solution or solutions. Metaheuristics get the best solutions using reasonable computation times, even for the largest instances. All the methods have been implemented within the FACOP platform (Framework for Applied Combinatorial Optimization Problems). Said platform is capable of incorporating new optimization algorithms for operational research problems related to decision-making in organizations and it is designed to address real cases in companies. Incorporating in this platform all the methodologies proposed in this Doctoral Thesis, brings the academic world closer to the business world. / Alfaro Fernández, P. (2023). Inteligencia computacional en la programación de la producción con recursos adicionales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198891

The thesis dwells about methodics of processing an order in the company: Hardening shop Frydrych s.r.o. while respecting all the demands on the technological process of thermal and thermo-chemical manipulation as annealing, tempering and cementing. On the bases of the analyse and documental procedures the thesis is unraveling a concept for elimination of absences in the sphere of processing the order also as booking, invoicing and evaluating.