MATHEMATICAL MODELLING AND SIMULATION OF WORKING OF AN ENTERPRIZE MANUFACTURING ELECTRIC MOTORS

Assembly of electric motor is a complex phenomenon. The phenomenon includes the worker who assembles the motor and his working environment such as the table on which he is working and chair on which he is sitting during the assembly. In addition to this, various parameters such as design of tools involved in assembly of electric motor, amount of energy worker puts in during the assembly, anthropometric data of the workers, working conditions such as humidity, temperature etc. also influence the productivity of assembly operation. Considering these parameters the two important aspects to be considered are productivity of electric motor along with the comforts to the workers. The aim of the work was to increase the productivity of electric motor assembly keeping in mind more convenience to the workers. Out of so many parameters mentioned above we would like to find out which of these parameters are most important for increasing the productivity and also reducing the human energy input. Simultaneously it would be interesting to know influence of one parameter over the other

A Hybrid Tabu/Scatter Search Algorithm for Simulation-Based Optimization of Multi-Objective Runway Operations Scheduling

As air traffic continues to increase, air traffic flow management is becoming more challenging to effectively and efficiently utilize airport capacity without compromising safety, environmental and economic requirements. Since runways are often the primary limiting factor in airport capacity, runway operations scheduling emerge as an important problem to be solved to alleviate flight delays and air traffic congestion while reducing unnecessary fuel consumption and negative environmental impacts. However, even a moderately sized real-life runway operations scheduling problem tends to be too complex to be solved by analytical methods, where all mathematical models for this problem belong to the complexity class of NP-Hard in a strong sense due to combinatorial nature of the problem. Therefore, it is only possible to solve practical runway operations scheduling problem by making a large number of simplifications and assumptions in a deterministic context. As a result, most analytical models proposed in the literature suffer from too much abstraction, avoid uncertainties and, in turn, have little applicability in practice. On the other hand, simulation-based methods have the capability to characterize complex and stochastic real-life runway operations in detail, and to cope with several constraints and stakeholders’ preferences, which are commonly considered as important factors in practice. This dissertation proposes a simulation-based optimization (SbO) approach for multi-objective runway operations scheduling problem. The SbO approach utilizes a discrete-event simulation model for accounting for uncertain conditions, and an optimization component for finding the best known Pareto set of solutions. This approach explicitly considers uncertainty to decrease the real operational cost of the runway operations as well as fairness among aircraft as part of the optimization process. Due to the problem’s large, complex and unstructured search space, a hybrid Tabu/Scatter Search algorithm is developed to find solutions by using an elitist strategy to preserve non-dominated solutions, a dynamic update mechanism to produce high-quality solutions and a rebuilding strategy to promote solution diversity. The proposed algorithm is applied to bi-objective (i.e., maximizing runway utilization and fairness) runway operations schedule optimization as the optimization component of the SbO framework, where the developed simulation model acts as an external function evaluator. To the best of our knowledge, this is the first SbO approach that explicitly considers uncertainties in the development of schedules for runway operations as well as considers fairness as a secondary objective. In addition, computational experiments are conducted using real-life datasets for a major US airport to demonstrate that the proposed approach is effective and computationally tractable in a practical sense. In the experimental design, statistical design of experiments method is employed to analyze the impacts of parameters on the simulation as well as on the optimization component’s performance, and to identify the appropriate parameter levels. The results show that the implementation of the proposed SbO approach provides operational benefits when compared to First-Come-First-Served (FCFS) and deterministic approaches without compromising schedule fairness. It is also shown that proposed algorithm is capable of generating a set of solutions that represent the inherent trade-offs between the objectives that are considered. The proposed decision-making algorithm might be used as part of decision support tools to aid air traffic controllers in solving the real-life runway operations scheduling problem

An efficient genetic algorithm application in assembly line balancing.

The main achievement of this research is the development of a genetic algorithm model as a solution approach to the single model assembly line balancing problem (SMALBP), considered a difficult combinatorial optimisation problem. This is accomplished by developing a genetic algorithm with a new fitness function and genetic operators. The novel fitness function is based on a new front-loading concept capable of yielding substantially improved and sometimes optimum solutions for the SMALBP. The new genetic operators include a modified selection technique, moving crossover point technique, rank positional weight based repair method and dynamic mutation technique. The moving crossover point technique addressed the issue of propagating best attributes from parents to offspring and also supports the forward loading process. The new selection technique was developed by modifying the original rank-based selection scheme. This eliminates the high selective pressure associate with the original rank-based technique. Furthermore, the modified selection technique allows the algorithm to run long enough, if required, without premature convergence and this feature is very useful for balancing more complex real world problems. The repair technique included in this model repairs a higher proportion of distorted chromosomes after crossover than previous methods. Moreover, a third innovative feature, a moving adjacent mutation technique, strengthens the forward loading procedure and accelerates convergence. The performance of the front-loading fitness function currently outperforms the published fitness functions and fifty-four published test cases generated from sixteen precedence networks are used to assess the overall performance of the model. Encompassing the new genetic algorithm concepts, forty-four test problems (81%) achieved the best solutions obtained by published techniques and twenty-four problems (44%) produced better results than the benchmark Hoffmann precedence procedure, the closest non-genetic algorithm method. The superiority of the genetic model over other heuristics is identified in this research and future developments of this genetic algorithm application for assembly line balancing problems is evident

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Control of transport dynamics in overlay networks

Transport control is an important factor in the performance of Internet protocols, particularly in the next generation network applications involving computational steering, interactive visualization, instrument control, and transfer of large data sets. The widely deployed Transport Control Protocol is inadequate for these tasks due to its performance drawbacks. The purpose of this dissertation is to conduct a rigorous analytical study on the design and performance of transport protocols, and systematically develop a new class of protocols to overcome the limitations of current methods. Various sources of randomness exist in network performance measurements due to the stochastic nature of network traffic. We propose a new class of transport protocols that explicitly accounts for the randomness based on dynamic stochastic approximation methods. These protocols use congestion window and idle time to dynamically control the source rate to achieve transport objectives. We conduct statistical analyses to determine the main effects of these two control parameters and their interaction effects. The application of stochastic approximation methods enables us to show the analytical stability of the transport protocols and avoid pre-selecting the flow and congestion control parameters. These new protocols are successfully applied to transport control for both goodput stabilization and maximization. The experimental results show the superior performance compared to current methods particularly for Internet applications. To effectively deploy these protocols over the Internet, we develop an overlay network, which resides at the application level to provide data transmission service using User Datagram Protocol. The overlay network, together with the new protocols based on User Datagram Protocol, provides an effective environment for implementing transport control using application-level modules. We also study problems in overlay networks such as path bandwidth estimation and multiple quickest path computation. In wireless networks, most packet losses are caused by physical signal losses and do not necessarily indicate network congestion. Furthermore, the physical link connectivity in ad-hoc networks deployed in unstructured areas is unpredictable. We develop the Connectivity-Through-Time protocols that exploit the node movements to deliver data under dynamic connectivity. We integrate this protocol into overlay networks and present experimental results using network to support a team of mobile robots

EXTENDING AND IMPROVING DESIGNS FOR LARGE-SCALE COMPUTER EXPERIMENTS

This research develops methods that increase the inventory of space-filling designs (SFDs) for large-scale computer-based experiments. We present a technique enabling researchers to add sequential blocks of design points effectively and efficiently to existing SFDs. We accomplish this through a quadratically constrained mixed-integer program that augments cataloged or computationally expensive designs by optimally permuting and stacking columns of an initial base design to minimize the maximum absolute pairwise correlation among columns in the new extended design. We extend many classes of SFDs to dimensions that are currently not easily obtainable. Adding new design points provides more degrees of freedom for building metamodels and assessing fit. The resulting extended designs have better correlation and space-filling properties than the original base designs and compare well with other types of SFDs created from scratch in the extended design space. In addition, through massive computer-based experimentation, we compare popular software packages for generating SFDs and provide insight into the methods and relationships among design measures of correlation and space-fillingness. These results provide experimenters with a broad understanding of SFD software packages, algorithms, and optimality criteria. Further, we provide a probability-distribution model for the maximum absolute pairwise correlation among columns in the widely used maximin Latin hypercube designs.Lieutenant Colonel, United States Marine CorpsApproved for public release. Distribution is unlimited

Exact and non-exact procedures for solving the response time variability problem (RTVP)

Premi extraordinari doctorat curs 2009-2010, àmbit d’Enginyeria IndustrialCuando se ha de compartir un recurso entre demandas (de productos, clientes, tareas, etc.) competitivas que requieren una atención regular, es importante programar el derecho al acceso del recurso de alguna forma justa de manera que cada producto, cliente o tarea reciba un acceso al recurso proporcional a su demanda relativa al total de las demandas competitivas. Este tipo de problemas de secuenciación pueden ser generalizados bajo el siguiente esquema. Dados n símbolos, cada uno con demanda di (i = 1,...,n), se ha de generar una secuencia justa o regular donde cada símbolo aparezca di veces. No existe una definición universal de justicia, ya que puede haber varias métricas razonables para medirla según el problema específico considerado. En el Problema de Variabilidad en el Tiempo de Respuesta, o Response Time Variability Problem (RTVP) en inglés, la injusticia o irregularidad de una secuencia es medida como la suma, para todos los símbolos, de sus variabilidades en las distancias en que las copias de cada símbolo son secuenciados. Así, el objetivo del RTVP es encontrar la secuencia que minimice la variabilidad total. En otras palabras, el objetivo del RTVP es minimizar la variabilidad de los instantes en que los productos, clientes o trabajos reciben el recurso necesario. Este problema aparece en una amplia variedad de situaciones de la vida real; entre otras, secuenciación en líneas de modelo-mixto bajo just-in-time (JIT), en asignación de recursos en sistemas computacionales multi-hilo como sistemas operativos, servidores de red y aplicaciones mutimedia, en el mantenimiento periódico de maquinaria, en la recolección de basura, en la programación de comerciales en televisión y en el diseño de rutas para agentes comerciales con múltiples visitas a un mismo cliente. En algunos de estos problemas la regularidad no es una propiedad deseable por sí misma, si no que ayuda a minimizar costes. De hecho, cuando los costes son proporcionales al cuadrado de las distancias, el problema de minimizar costes y el RTVP son equivalentes. El RTVP es muy difícil de resolver (se ha demostrado que es NP-hard). El tamaño de las instancias del RTVP que pueden ser resueltas óptimamente con el mejor método exacto existente en la literatura tiene un límite práctico de 40 unidades. Por otro lado, los métodos no exactos propuestos en la literatura para resolver instancias mayores consisten en heurísticos simples que obtienen soluciones rápidamente, pero cuya calidad puede ser mejorada. Por tanto, los métodos de resolución existentes en la literatura son insuficientes. El principal objetivo de esta tesis es mejorar la resolución del RTVP. Este objetivo se divide en los dos siguientes subobjetivos : 1) aumentar el tamaño de las instancias del RTVP que puedan ser resueltas de forma óptima en un tiempo de computación práctico, y 2) obtener de forma eficiente soluciones lo más cercanas a las óptimas para instancias mayores. Además, la tesis tiene los dos siguientes objetivos secundarios: a) investigar el uso de metaheurísticos bajo el esquema de los hiper-heurísticos, y b) diseñar un procedimiento sistemático y automático para fijar los valores adecuados a los parámetros de los algoritmos. Se han desarrollado diversos métodos para alcanzar los objetivos anteriormente descritos. Para la resolución del RTVP se ha diseñado un método exacto basado en la técnica branch and bound y el tamaño de las instancias que pueden resolverse en un tiempo práctico se ha incrementado a 55 unidades. Para instancias mayores, se han diseñado métodos heurísticos, metaheurísticos e hiper-heurísticos, los cuales pueden obtener soluciones óptimas o casi óptimas rápidamente. Además, se ha propuesto un procedimiento sistemático y automático para tunear parámetros que aprovecha las ventajas de dos procedimientos existentes (el algoritmo Nelder & Mead y CALIBRA).When a resource must be shared between competing demands (of products, clients, jobs, etc.) that require regular attention, it is important to schedule the access right to the resource in some fair manner so that each product, client or job receives a share of the resource that is proportional to its demand relative to the total of the competing demands. These types of sequencing problems can be generalized under the following scheme. Given n symbols, each one with demand di (i = 1,...,n), a fair or regular sequence must be built in which each symbol appears di times. There is not a universal definition of fairness, as several reasonable metrics to measure it can be defined according to the specific considered problem. In the Response Time Variability Problem (RTVP), the unfairness or the irregularity of a sequence is measured by the sum, for all symbols, of their variabilities in the positions at which the copies of each symbol are sequenced. Thus, the objective of the RTVP is to find the sequence that minimises the total variability. In other words, the RTVP objective is to minimise the variability in the instants at which products, clients or jobs receive the necessary resource. This problem appears in a broad range of real-world areas. Applications include sequencing of mixed-model assembly lines under just-in-time (JIT), resource allocation in computer multi-threaded systems such as operating systems, network servers and media-based applications, periodic machine maintenance, waste collection, scheduling commercial videotapes for television and designing of salespeople's routes with multiple visits, among others. In some of these problems the regularity is not a property desirable by itself, but it helps to minimise costs. In fact, when the costs are proportional to the square of the distances, the problem of minimising costs and the RTVP are equivalent. The RTVP is very hard to be solved (it has been demonstrated that it is NP-hard). The size of the RTVP instances that can be solved optimally with the best exact method existing in the literature has a practical limit of 40 units. On the other hand, the non-exact methods proposed in the literature to solve larger instances are simple heuristics that obtains solutions quickly, but the quality of the obtained solutions can be improved. Thus, the solution methods existing in the literature are not enough to solve the RTVP. The main objective of this thesis is to improve the resolution of the RTVP. This objective is split in the two following sub-objectives: 1) to increase the size of the RTVP instances that can be solved optimally in a practical computing time; and 2) to obtain efficiently near-optimal solutions for larger instances. Moreover, the thesis has the following two secondary objectives: a) to research the use of metaheuristics under the scheme of hyper-heuristics, and b) to design a systematic, hands-off procedure to set the suitable values of the algorithm parameters. To achieve the aforementioned objectives, several procedures have been developed. To solve the RTVP an exact procedure based on the branch and bound technique has been designed and the size of the instances that can be solved in a practical time has been increased to 55 units. For larger instances, heuristic, heuristic, metaheuristic and hyper-heuristic procedures have been designed, which can obtain optimal or near-optimal solutions quickly. Moreover, a systematic, hands-off fine-tuning method that takes advantage of the two existing ones (Nelder & Mead algorithm and CALIBRA) has been proposed.Award-winningPostprint (published version