AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Proactive-reactive, robust scheduling and capacity planning of deconstruction projects under uncertainty

A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

Proactive-reactive, robust scheduling and capacity planning of deconstruction projects under uncertainty

A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution

Method to integrate the microbusinesses from the textile sector in Bogota based on an association and allocation approach

La asociación entre microempresas es una estrategia para lograr objetivos comunes, ya que ayuda a consolidar algunas operaciones comerciales en el mercado. La asociación brinda la oportunidad de fortalecer capacidades y compartir recursos sin fusionarse. Sin embargo, en algunos casos, el proceso para crear una asociación productiva se realiza bajo los criterios y la experiencia de cada organización, en lugar de una herramienta cuantitativa para la toma de decisiones. Por lo tanto, este estudio desarrolla un método, implementado en la herramienta computacional Visual Basic for Applications, basado en un algoritmo genético, que involucra la ponderación de múltiples criterios a través de AHP, que organiza las microempresas en grupos empresariales y reglas de despacho para asignar la producción y las tareas dentro de la asociación (intra-cluster e inter-cluster). Los resultados obtenidos en la etapa de asociación de la heurística se validan contra las simulaciones realizadas utilizando el modelo matemático para la asociación, y se observa una buena conformación de los clusters. El rendimiento alcanzado en la etapa de asignación del método y la programación posterior se evalúan en comparación con la solución óptima proporcionada por el modelo matemático para la asignación general y con las medidas de rendimiento para la asignación dentro del grupo, respectivamente. La solución apunta a una distribución eficiente y equilibrada de órdenes de producción entre los grupos de microempresas. En este artículo, se presenta la aplicación del método a un caso de estudio de talleres informales de costura ubicados en Usme, Bogotá (Colombia).Association among microbusinesses is a strategy to achieve common objectives, as it helps to consolidate some business operations in the marketplace. Association provides the opportunity to strengthen their capabilities and share resources without merging. However, in some cases, the process to create a productive association is done under the criteria and experience of each organization, rather than on a quantitative tool for decision-making. Therefore, this study develops a method, implemented in the computational tool Visual Basic for Applications, based on a genetic algorithm, involving the weighting of multiple criteria through AHP, that organizes microbusinesses into business clusters, and dispatching rules to allocate production and tasks within the associates (intra-cluster and inter-cluster). The results obtained by the association stage of the heuristic are validated against simulations performed using the mathematical model for association, and a good cluster conformation is observed. The performance reached in the allocation stage of the method and the subsequently scheduling are evaluated in comparison with the optimal solution provided by the mathematical model for general allocation and with the performance measures for allocation inside the cluster, respectively. The solution targets efficient and balanced production order distribution among the microbusiness clusters. In this paper, is presented the application of the method to a case study of informal sewing workshops located in Usme, Bogota (Colombia).Ingeniero (a) IndustrialPregrad

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

Technology and Management Applied in Construction Engineering Projects

This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering

An agile and adaptive holonic architecture for manufacturing control

In the last decades significant changes in the manufacturing environment have been noticed: moving from a local economy towards a global economy, with markets asking for products with high quality at lower costs, highly customised and with short life cycle. In this environment, the manufacturing enterprises, to avoid the risk to lose competitiveness, search to answer more closely to the customer demands, by improving their flexibility and agility, while maintaining their productivity and quality. Actually, the dynamic response to emergence is becoming a key issue, due to the weak response of the traditional manufacturing control systems to unexpected disturbances, mainly because of the rigidity of their control architectures. In these circumstances, the challenge is to develop manufacturing control systems with autonomy and intelligence capabilities, fast adaptation to the environment changes, more robustness against the occurrence of disturbances, and easier integration of manufacturing resources and legacy systems. Several architectures using emergent concepts and technologies have been proposed, in particular those based in the holonic manufacturing paradigm. Holonic manufacturing is a paradigm based in the ideas of the philosopher Arthur Koestler, who proposed the word holon to describe a basic unit of organisation in biological and social systems. A holon, as Koestler devised the term, is an identifiable part of a (manufacturing) system that has a unique identity, yet is made up of sub-ordinate parts and in turn is part of a larger whole. The introduction of the holonic manufacturing paradigm allows a new approach to the manufacturing problem, bringing the advantages of modularity, decentralisation, autonomy, scalability, and re-use of software components. This dissertation intends to develop an agile and adaptive manufacturing control architecture to face the current requirements imposed to the manufacturing enterprises. The architecture proposed in this dissertation addresses the need for the fast reaction to disturbances at the shop floor level, increasing the agility and flexibility of the enterprise, when it works in volatile environments, characterised by the frequent occurrence of unexpected disturbances. The proposed architecture, designated by ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), is based in the holonic manufacturing paradigm, build upon autonomous and cooperative holons, allowing the development of manufacturing control applications that present all the features of decentralised and holonic systems. ADACOR holonic architecture introduces an adaptive control that balances dynamically between a more centralised structure and a more decentralised one, allowing to combine the global production optimisation with agile reaction to unexpected disturbances. Nas últimas décadas têm-se assistido a mudanças significativas no ambiente de fabrico: evoluindo de uma economia local para um economia global, com os mercados a procurar produtos com elevada qualidade a baixos preços, altamente customizados e com um ciclo de vida curto. Neste ambiente, as empresas de manufactura, para evitar o risco de perda de competitividade, procuram responder às solicitações dos clientes, melhorando a sua flexibilidade e agilidade, mantendo os mesmos índices de produtividade e qualidade. Na verdade, a resposta dinâmica à emergência está a tornar-se num assunto chave, devido `a fraca resposta a perturbações que os sistemas de controlo de fabrico tradicionais apresentam, principalmente devido à rigidez das suas arquitecturas de controlo. Nestas circunstâncias, é fundamental o desenvolvimento de sistemas de controlo de fabrico com capacidades de autonomia e inteligência, rápida adaptação às mudanças, maior robustez à ocorrência de perturbações e fácil integração de recursos físicos e sistemas legados. Diversas arquitecturas usando conceitos e tecnologias emergentes têm sido propostas, em particular algumas baseadas no paradigma da produção holónica. O paradigma da produção holónica é inspirado nas ideias de Arthur Koestler, que propôs a palavra holon para descrever uma unidade básica de organização de sistemas biológicos e sociais. Um holon, de acordo com a definição de Koestler, é uma parte identificável do sistema com identidade única, composta por sub-partes e fazendo simultaneamente parte do todo. A introdução do paradigma da produção holónica permite uma nova abordagem aos sistemas de controlo de fabrico, trazendo vantagens de modularidade, descentralização, autonomia, escalabilidade e reutilização de componentes. Esta dissertação pretende desenvolver uma arquitectura de controlo ágil e adaptativa que suporte os requisitos actuais impostos `as empresas de manufactura. A arquitectura proposta visa a necessidade de uma reacção rápida a perturbações, ao nível da planta fabril, melhorando a flexibilidade e agilidade da empresa quando esta opera em ambientes voláteis, caracterizados pela ocorrência frequente de perturbações inesperadas. A arquitectura proposta, designada por ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), é baseada no paradigma da produção holónica e construída sobre holons autónomos e cooperativos, permitindo o desenvolvimento de aplicações de controlo de fabrico que apresentem todas as características dos sistemas descentralizados e holónicos. A arquitectura holónica ADACOR introduz um controlo adaptativo que balança dinamicamente entre uma estrutura de controlo mais centralizada e uma mais descentralizada, permitindo combinar a optimização da produção com a ágil reacção a perturbações

Exact Integer Programming Approaches to Sequential Instruction Scheduling and Offset Assignment

The dissertation at hand presents the main concepts and results derived when studying the optimal solution of two NP-hard compiler optimization problems, namely instruction scheduling and offset assignment, by means of integer programming. It is the outcome of several years of research as an assistant at Michael Jünger's computer science chair in Cologne, with the particular aim to apply exact mathematical optimization techniques to real-world problems arising in the domain of technical computer science. The two problems studied are rather unrelated apart from the fact that they both take place during the machine code generation phase of a compiler and deal with the handling of limited resources. Instruction scheduling is about the assignment of issue clock cycles to instructions in the presence of precedence, latency, and resource constraints such that the total time needed to execute all the instructions is minimized. Offset assignment deals with storage layouts of program variables and the efficient use of address registers for accesses to these variables. The objective is to employ specialized instructions in order to minimize the overhead caused by address computations. While instruction scheduling needs to be carried out by almost every present compiler irrespective of the processor architecture, the offset assignment problem occurs mainly in compilers for highly specialized processor designs. Instruction scheduling is a well-studied field where several exact and heuristic approaches have been developed and experimentally evaluated in the past. In this thesis, we concentrate on the basic-block instruction scheduling problem for single-issue processors. Basic blocks are program fragments with no side-entrances and -exits, i.e., every instruction of a basic block needs to be executed before the control flow may leave it and enter another basic block. Single-issue processors are capable of starting the execution of exactly one instruction per clock cycle. A number of techniques to preprocess instances of the basic-block instruction scheduling problem were proposed in the literature and are, with emphasis on the more recent ones that arose since the year 2000, thoroughly reviewed in this thesis. They finally led to a constraint programming approach in 2006 that was shown to solve about 350,000 instances to optimality and where some of these instances comprised up to about 2,500 instructions. The last attempt to tackle the problem using integer programming however dates to a time prior to the publication of the latest preprocessing advances. While being successful on a set of instances that impose very restrictive latency constraints, it was shown to be unable to solve hundreds of instances from the aforementioned benchmark set that comprises also large and varying latencies. In addition, the previous integer programming models were almost all based on so-called time-indexed formulations where decision variables model an explicit assignment of instructions to clock cycles. In this thesis, a completely different and novel approach is taken based on the linear ordering problem, a well-studied combinatorial optimization problem. The new models lead to alternative characterizations of the feasible solutions to the basic-block instruction scheduling problem. These facilitate the employment of advanced integer programming methodologies, in particular the design of branch-and-cut algorithms that can handle larger instances. The formulations are further extended by additional inequalities that can be used as cutting planes. Combined with the preprocessing routines that are partially extended and improved as well, the respective solver implementation eventually turned out to be competitive to the constraint programming method. Reaching this point has taken some years and this thesis presents not only the derived models but also several ideas and byproducts that arose in the meantime, and that can help and inspire researchers even if they aim at the application of different solution methodologies. The starting point regarding the offset assignment problem was a different one because especially exact solution approaches were rather rare prior to the models presented in this thesis. The offset assignment problem arose in the 1990s and is considered in several variants that are of theoretical and practical interest. In the simplest one, a processor is assumed to provide only a single address register and only very restricted possibilities to avoid address computation overhead. However, even this simplest variant, that may serve as a building block for the more complex ones, is already NP-hard and has been studied mainly from a heuristic point of view. The few existing exact solution approaches were not capable to solve moderately sized instances so that the quality of heuristic solutions relative to the optimum was hardly known at all. Again, the inspection of the combinatorial structure of the various problem variants turned out to be the key for designing branch-and-cut implementations that can profit from knowledge about related combinatorial optimization problems. The implementation targeting the simple problem variant was the first capable to optimally solve the majority of about 3,000 instances collected in a standard benchmark set. The method could then be further generalized in two steps. First, in a collaboration with Roberto Castañeda Lozano, additional techniques could be incorporated into the approach in order to handle multiple address registers. Fortunately, the methods could then even be further extended to as well deal with more flexible addressing capabilities. In this way, the thesis at hand does not only answer the question how large the address computation overhead can be when using heuristics, but as well presents first results that allow to analyze the impact of the mentioned increased addressing capabilities on the runtime performance and size of real-world programs