Algoritam planiranja operacija "flow shop" u cilju smanjivanja vremena izvršenja kod problema n-poslova i m-strojeva

In multi stage job problems, simple priority dispatching rules such as shortest processing time (SPT) and earliest due date (EDD) can be used to obtain solutions of minimum total processing time, but may not sometimes give sequences as expected that are close to optimal. The Johnson\u27s algorithm is especially popular among analytical approaches that are used for solving n-jobs, 2-machines sequence problem. In this paper the presented algorithm is based on converting an m-machine problem to a 2-machine problem. Based on testing and comparison with other relevant methods, the proposed algorithm is offered as a competitive alternative for practical application when solving n-jobs and m-machines problems.U problemima posla s više faza, mogu se koristiti jednostavna prioritetna dispečerska pravila kao što su najkraće vrijeme obrade (PT) i najraniji datum dospijeća (EDD) za dobivanje rješenja najmanjega ukupnog vremena obrade. Međutim, ona ponekad ne daju slijed za koji se očekuje da je blizu optimalnom. Johnsonov algoritam je posebno popularan među analitičkim pristupima koji se koriste za rješavanje problema slijeda n-poslova i 2-stroja. Algoritam prikazan u ovom radu se temelji na pretvaranju problema m-strojeva u problem 2-stroja. Na temelju ispitivanja i usporedbe s drugim relevantnim metodama, predloženi algoritam se nudi kao konkurentna alternativa za praktičnu primjenu pri rješavanju problema n-poslova i m-strojeva

Diseño de una metodología basada en técnicas inteligentes para la distribución de procesos Académicos en ambientes de trabajo job shop.

[ESP] La programación de horarios dentro de las instituciones educativas ha sido examinada desde diversas perspectivas, principalmente a nivel universitario. Sin embargo, se ha dejado de lado el problema de asignación de horarios en las instituciones de educación básica y media, en las cuales es necesario el establecimiento de múltiples parámetros que permitan una asignación que facilite la organización de restricciones especiales que favorezcan los momentos del aprendizaje de acuerdo a las necesidades de cada una de las áreas del conocimiento, sin afectar una equitativa repartición en la carga de los docentes y sin sobrepasar los límites de horas diarias y semanales que son necesarias dentro de cada materia. A diferencia de la asignación de horarios universitarios, los horarios escolares tienen un enfoque orientado a las clases y no a los estudiantes, por lo cual la carga académica se programa de una manera intensiva en periodos de una jornada diaria, para un grupo de estudiantes que deben cursar unos contenidos estructurados en diferentes áreas y repartidos en intensidades no superiores a las dos horas diarias en la misma asignatura. De esta manera, la planta física también cumple con la orientación a las clases, por lo cual los salones se asignan de forma permanente a un mismo grupo de estudiantes y se propicia de una manera sistemática la rotación de los docentes por cada una de las aulas según la distribución que se haga de la carga en la respectiva programación. En cuanto a la disponibilidad de los maestros, se da por hecho que no hay ningún tipo de conflicto en la asignación horaria durante la jornada, y que deben dictar un número mínimo de horas durante la programación semanal

Aplicação de Uma Nova Heurística em Problemas de Job Shop com Tempo Variável Dependente da Sequência

O Planejamento e Controle da Produção é uma área de estudo que pode, juntamente à Pesquisa Operacional e a modelagem matemática, otimizar o planejamento da produção. A programação da produção é ponto crucial na determinação de como sequenciar as tarefas pelas máquinas que as mesmas devem passar para então chegar ao produto final. No ambiente das oficinas de máquina pode-se considerar um possível tempo de preparação da máquina antes de receber a próxima tarefa, e este tempo depende da última tarefa sequenciada nesta máquina, o problema torna-se ainda maior e mais complexo. Para resolver este problema, este trabalho tem como objetivo aplicar uma heurística que busca minimizar o tempo total de trabalho na situação descrita. Esta heurística é implementada e testada para problemas de diversos tamanhos e os resultados obtidos são satisfatórios

Artificial intelligence effectiveness in job shop environments

The aim of this paper is to define a new methodology that allows the comparison of the effectiveness among some of the major artificial intelligence techniques (random technique, taboo search, data mining, evolutionary algorithms). This methodology is applied in the sequencing production process in job shop environments, in a problem with N orders, and M machines, where each of the orders must pass through every machine regardless of its turn. These techniques are measured by the variables of total makespan time, total idle time, and machine utilization percentage. Initially, a theoretical review was conducted and showed the usefulness and effectiveness of artificial intelligence in the sequencing production processes. Subsequently and based on the experiments presented, the obtained results showed that these techniques have an effectiveness higher than 95%, with a confidence interval of 99.5% measured by the variables under study

Reduction of carbon emission and total late work criterion in job shop scheduling by applying a multi-objective imperialist competitive algorithm

New environmental regulations have driven companies to adopt low-carbon manufacturing. This research is aimed at considering carbon dioxide in the operational decision level where limited studies can be found, especially in the scheduling area. In particular, the purpose of this research is to simultaneously minimize carbon emission and total late work criterion as sustainability-based and classical-based objective functions, respectively, in the multiobjective job shop scheduling environment. In order to solve the presented problem more effectively, a new multiobjective imperialist competitive algorithm imitating the behavior of imperialistic competition is proposed to obtain a set of non-dominated schedules. In this work, a three-fold scientific contribution can be observed in the problem and solution method, that are: (1) integrating carbon dioxide into the operational decision level of job shop scheduling, (2) considering total late work criterion in multi-objective job shop scheduling, and (3) proposing a new multi-objective imperialist competitive algorithm for solving the extended multi-objective optimization problem. The elements of the proposed algorithm are elucidated and forty three small and large sized extended benchmarked data sets are solved by the algorithm. Numerical results are compared with two well-known and most representative metaheuristic approaches, which are multi-objective particle swarm optimization and non-dominated sorting genetic algorithm II, in order to evaluate the performance of the proposed algorithm. The obtained results reveal the effectiveness and efficiency of the proposed multi-objective imperialist competitive algorithm in finding high quality non-dominated schedules as compared to the other metaheuristic approache

Otimização do tempo total de trabalho na programação da produção em oficina de máquinas com tempo de preparação dependente da sequência

Orientador : Prof. Dr. Arinei Carlos Lindbeck SilvaTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 10/12/2014Inclui referênciasÁrea de concentração: Programação matemáticaResumo: O planejamento da produção de uma indústria _e ponto fundamental na busca de bons resultados para metas estabelecidas e maximizar lucros. Para tal, o Planejamento e Controle da Produção e uma área de estudo que pode, com auxílio da Pesquisa Operacional e seus modelos matemáticos, otimizar diversos objetivos. Dentre as diversas decisões a serem tomadas dentro da indústria, uma e crucial para o sucesso ou não: a programação da produção, através da determinação de como sequenciar as tarefas pelas máquinas que as mesmas devem passar para então chegar ao produto final. São diversos ambientes descritos na literatura, sendo o mais abrangente a usina de máquinas. E quando neste ambiente, considera-se um possível tempo de preparação da maquina antes de receber a próxima tarefa, e este tempo depende da ultima tarefa sequenciada nesta máquina, o problema torna-se ainda maior e mais complexo. Para resolver este problema, este trabalho tem como objetivo apresentar uma nova heurística que busca minimizar o tempo total de trabalho na situação descrita. Esta heurística e implementada e testada para problemas de diversos tamanhos e os resultados obtidos são satisfatórios. Palavras-chave: Programação da Produção, Usina de maquinas, Tempo de preparação, Dependência da sequência.Abstract: An industry's planning of production is a fundamental area when seeking the best results for reaching established goals and maximizing profits. For that, with the help of Operational Research and its mathematical models, the planning and controlling of production is an area of study that can optimize many deferent areas. Amongst all these decisions made in the industry, one of them is quintessential in determining whether one succeeds or fails inside the industrial market - the scheduling of the production, through deciding how to sequence the tasks of the machines through which the product undergoes until it reaches its final state, completed and assembled. For this, there are many deferent environments in which machine sequencing is needed, but the most encompassing of them is the job shop. In this type of environment, each machine needs some sort of preparation prior to performing a certain task, and this preparation is dependant on the task that was previously performed by that machine - a matter which further complicates deciding the right sequencing. To solve this problem, this study presents a new heuristic that seeks to minimize the total time required for a complete a task similar to the one described earlier - one that considers a set of tasks with preparation dependant on the previous task performed. This heuristic is implemented and tested on several deferent problems of varying size, all of which show very successful results. Key-words: Scheduling, Job shop, Setup time, Sequence dependence

Disminución de la mortalidad académica en instituciones de educación básica y media mediante el empleo de técnicas inteligentes en la asignación de horarios

Esta investigación plantea la solución del problema de programación de horarios escolares bajo las características de la escuela pública colombiana incluyendo como factor primordial dentro del proceso de optimización, la ubicación horaria de las asignaturas en función de los ritmos cognitivos que presentan los estudiantes durante la jornada escolar. Para ello, se presenta el desarrollo de una aplicación en la cual se implementaron tres diferentes técnicas inteligentes a través de los cuales se busca la minimización de una función de evaluación que representa la calidad de la solución de acuerdo al enfoque establecido. Los resultados muestran una mayor eficiencia del algoritmo NSGA-II en comparación con los otros dos métodos aplicados al mismo problema y evaluados con la misma métrica. A nivel experimental, la metodología evidencia que los grupos programados mediante la orientación descrita presentan una reducción en los niveles de mortalidad académicaAbstract : This research raises the solution to school timetabling problem under the characteristics of Colombian public school including as a primary factor in the optimization process, the time location of the subjects according to cognitive rhythms presented by students during the school day. For this purpose, a development application is presented in which three different techniques were implemented through which the minimization for a Fitness function is looked for that represents the quality of the solution according to the established approach. The results show a higher efficiency of the NSGA-II algorithm compared to the other two methods applied to the same problem and evaluated with the same metric. At the experimental level, the methodology shows that the programmed groups through the guidance described show a reduction in the academic mortality levelsMaestrí

Development of a Multi-Objective Scheduling System for Complex Job Shops in a Manufacturing Environment

In many sectors of commercial operation, the scheduling of workflows and the allocation of resources at an optimum time is critical; for effective and efficient operation. The high degree of complexity of a “Job Shop” manufacturing environment, with sequencing of many parallel orders, and allocation of resources within multi-objective operational criteria, has been subject to several research studies. In this thesis, a scheduling system for optimizing multi-objective job shop scheduling problems was developed in order to satisfy different production system requirements. The developed system incorporated three different factors; setup times, alternative machines and release dates, into one model. These three factors were considered after a survey study of multiobjective job shop scheduling problems. In order to solve the multi-objective job shop scheduling problems, a combination of genetic algorithm and a modified version of a very recent and computationally efficient approach to non-dominated sorting solutions, called “efficient non-dominated sort using the backward pass sequential strategy”, was applied. In the proposed genetic algorithm, an operation based representation was designed in the matrix form, which can preserve features of the parent after the crossover operator without repairing the solution. The proposed efficient non-dominated sort using the backward pass sequential strategy was employed to determine the front, to which each solution belongs. The proposed system was tested and validated with 20 benchmark problems after they have been modified. The experimental results show that the proposed system was effective and efficient to solve multi-objective job shop scheduling problems in terms of solution quality

A study on flexible flow shop and job shop scheduling using meta-heuristic approaches

Scheduling aims at allocation of resources to perform a group of tasks over a period of time in such a manner that some performance goals such as flow time, tardiness, lateness, and makespan can be minimized. Today, manufacturers face the challenges in terms of shorter product life cycles, customized products and changing demand pattern of customers. Due to intense competition in the market place, effective scheduling has now become an important issue for the growth and survival of manufacturing firms. To sustain in the current competitive environment, it is essential for the manufacturing firms to improve the schedule based on simultaneous optimization of performance measures such as makespan, flow time and tardiness. Since all the scheduling criteria are important from business operation point of view, it is vital to optimize all the objectives simultaneously instead of a single objective. It is also essentially important for the manufacturing firms to improve the performance of production scheduling systems that can address internal uncertainties such as machine breakdown, tool failure and change in processing times. The schedules must meet the deadline committed to customers because failure to do so may result in a significant loss of goodwill. Often, it is necessary to reschedule an existing plan due to uncertainty event like machine breakdowns. The problem of finding robust schedules (schedule performance does not deteriorate in disruption situation) or flexible schedules (schedules expected to perform well after some degree of modification when uncertain condition is encountered) is of utmost importance for real world applications as they operate in dynamic environments

An on-demand fixture manufacturing cell for mass customisation production systems.

Master of Science in Engineering. University of KwaZulu-Natal, Durban, 2017.Increased demand for customised products has given rise to the research of mass customisation production systems. Customised products exhibit geometric differences that render the use of standard fixtures impractical. Fixtures must be configured or custom-manufactured according to the unique requirements of each product. Reconfigurable modular fixtures have emerged as a cost-effective solution to this problem. Customised fixtures must be made available to a mass customisation production system as rapidly as parts are manufactured. Scheduling the creation/modification of these fixtures must now be treated together with the production scheduling of parts on machines. Scheduling and optimisation of such a problem in this context was found to be a unique avenue of research. An on-demand Fixture Manufacturing Cell (FxMC) that resides within a mass customisation production system was developed. This allowed fixtures to be created or reconfigured on-demand in a cellular manufacturing environment, according to the scheduling of the customised parts to be processed. The concept required the research and development of such a cell, together with the optimisation modelling and simulation of this cell in an appropriate manufacturing environment. The research included the conceptualisation of a fixture manufacturing cell in a mass customisation production system. A proof-of-concept of the cell was assembled and automated in the laboratory. A three-stage optimisation method was developed to model and optimise the scheduling of the cell in the manufacturing environment. This included clustering of parts to fixtures; optimal scheduling of those parts on those fixtures; and a Mixed Integer Linear Programming (MILP) model to optimally synchronise the fixture manufacturing cell with the part processing cell. A heuristic was developed to solve the MILP problem much faster and for much larger problem sizes – producing good, feasible solutions. These problems were modelled and tested in MATLAB®. The cell was simulated and tested in AnyLogic®. The research topic is beneficial to mass customisation production systems, where the use of reconfigurable modular fixtures in the manufacturing process cannot be optimised with conventional scheduling approaches. The results showed that the model optimally minimised the total idle time of the production schedule; the heuristic also provided good, feasible solutions to those problems. The concept of the on-demand fixture manufacturing cell was found to be capable of facilitating the manufacture of customised products