16 research outputs found

    A New Approach to Blending and Loading Problem of Molten Aluminum

    Get PDF
    The problems of blending electrolyzer and multi-constraint optimization of electrolytic aluminum scheduling in the electrolytic aluminum production process were addressed. Based on a mathematical model analysis, a novel hybrid optimization algorithm is proposed for optimization of blending together the molten aluminum in different electrolytic cells. An affinity degree function was designed to represent the path of aluminum scheduling. The mutation operators were designed to implement the transformation of electrolyzer combination and change the route of loading. A typical optimization example from an aluminum plant in northwest China is given in this paper, the results of which demonstrate the effectiveness of the proposed method

    A Metaheuristic Compendium for Scheduling Problems

    Get PDF
    The flexible job shop scheduling problem (FJSSP) is a difficult and complex problem, proved to be NP-hard, in manufacturing environments, because it has to assign each operation to the appropriate machine besides sequencing operations on machines. Due to that complexity, metaheuristics became the best choice to solve in practice this kind of problem. Therefore, the aim of this paper is to offer a reliable compendium in order to cover a wide algorithmic spectrum of different techniques. Further, a study of their accuracy and computational effort is carried out in order to achieve a behavior comparison. This paper shows different algorithmic trends that can be observed through this analysis.Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI

    Un Squirrel Search Algorithm discreto aplicado al problema Job Shop con operadores calificados

    Get PDF
    Introduction: The Job Shop problem With Skilled Operators (JSSO) is an extension of the classic Job Shop in which, an operation must be executed by a limited set of workers, aiming to minimize jobs total termination time or Makespan. This situation can represent different applications in daily life. JSSO is a complex problem and its classified as NP-HARD.. Objective: In this article, the JSSO problem is addressed. It is made by adapting an algorithm known as Squirrel Search Algorithm (SSA). Method:  A discrete encoding scheme is proposed for the SSA algorithm and the Smallest Position Value (SPV) method are used. Also, solutions that can violate the precedent relationships are corrected with the Valid Particle Generator (VPG) method, which guarantees feasible solutions. Two versions of the algorithm were tested in 28 instances proposed in the literature to valid their performance. Results: Computer experiments show that the proposed algorithms reach optimal solutions in 25 and 28 analyzed instances. In addition, for the instances where optimality was not achieved, the average gap does not exceed the 2% for both versions of the proposed algorithms. Conclusions: The proposed encoding scheme guarantees the discretization of the algorithms, generating solutions that converge towards the optimum. In addition, the proposed encoding allows natural use of movement operators originally proposed for the algorithms used. Performance obtained by the algorithms is adequate and of high quality.Introducción: El problema Job Shop Con Operadores Calificados o Job Shop With Skilled Operators (JSSO) es una extensión del problema clásico Job Shop en el cual, una operación debe ser ejecutada por un conjunto limitados de trabajadores, con el objetivo de minimizar el tiempo de terminación total de los trabajos o Makespan, situación que puede representar distintas aplicaciones en la vida cotidiana. Es un problema complejo y es catalogado como NP-HARD. Objetivo: En este artículo, se aborda el problema JSSO desde la adaptación de un algoritmo conocido como Squirrel Search Algorithm (SSA). Metodología: Se propone un esquema de codificación discreto para el algoritmo SSA utilizando el método Smallest Position Value (SPV). Además, para evitar soluciones que violen las relaciones de precedencia; se corrigen con el método Valid Particle Generator (VPG), el cual garantiza soluciones factibles. Dos versiones del algoritmo se colocan a prueba en 28 instancias propuesta en la literatura para validar su rendimiento. Resultados: Los experimentos computacionales realizados muestran que los dos algoritmos propuestos alcanzan soluciones óptimas en 25 de las 28 instancias analizadas. Además, para las instancias en donde no se logró soluciones óptimas, el gap promedio no supera el 2% para ambas versiones de los algoritmos propuestos. Conclusiones: El esquema de codificación propuesto garantiza la discretización del algoritmo, generando soluciones que convergen hacia el óptimo. Además, la codificación propuesta, permite utilizar de manera natural los operadores de movimiento propuestos originalmente para el algoritmo utilizado. El rendimiento obtenido por los algoritmos es adecuado y de alta calidad

    Un Squirrel Search Algorithm discreto aplicado al problema Job Shop con operadores calificados

    Get PDF
    Introduction: The Job Shop problem With Skilled Operators (JSSO) is an extension of the classic Job Shop in which, an operation must be executed by a limited set of workers, aiming to minimize jobs total termination time or Makespan. This situation can represent different applications in daily life. JSSO is a complex problem and its classified as NP-HARD.. Objective: In this article, the JSSO problem is addressed. It is made by adapting an algorithm known as Squirrel Search Algorithm (SSA). Method:  A discrete encoding scheme is proposed for the SSA algorithm and the Smallest Position Value (SPV) method are used. Also, solutions that can violate the precedent relationships are corrected with the Valid Particle Generator (VPG) method, which guarantees feasible solutions. Two versions of the algorithm were tested in 28 instances proposed in the literature to valid their performance. Results: Computer experiments show that the proposed algorithms reach optimal solutions in 25 and 28 analyzed instances. In addition, for the instances where optimality was not achieved, the average gap does not exceed the 2% for both versions of the proposed algorithms. Conclusions: The proposed encoding scheme guarantees the discretization of the algorithms, generating solutions that converge towards the optimum. In addition, the proposed encoding allows natural use of movement operators originally proposed for the algorithms used. Performance obtained by the algorithms is adequate and of high quality.Introducción: El problema Job Shop Con Operadores Calificados o Job Shop With Skilled Operators (JSSO) es una extensión del problema clásico Job Shop en el cual, una operación debe ser ejecutada por un conjunto limitados de trabajadores, con el objetivo de minimizar el tiempo de terminación total de los trabajos o Makespan, situación que puede representar distintas aplicaciones en la vida cotidiana. Es un problema complejo y es catalogado como NP-HARD. Objetivo: En este artículo, se aborda el problema JSSO desde la adaptación de un algoritmo conocido como Squirrel Search Algorithm (SSA). Metodología: Se propone un esquema de codificación discreto para el algoritmo SSA utilizando el método Smallest Position Value (SPV). Además, para evitar soluciones que violen las relaciones de precedencia; se corrigen con el método Valid Particle Generator (VPG), el cual garantiza soluciones factibles. Dos versiones del algoritmo se colocan a prueba en 28 instancias propuesta en la literatura para validar su rendimiento. Resultados: Los experimentos computacionales realizados muestran que los dos algoritmos propuestos alcanzan soluciones óptimas en 25 de las 28 instancias analizadas. Además, para las instancias en donde no se logró soluciones óptimas, el gap promedio no supera el 2% para ambas versiones de los algoritmos propuestos. Conclusiones: El esquema de codificación propuesto garantiza la discretización del algoritmo, generando soluciones que convergen hacia el óptimo. Además, la codificación propuesta, permite utilizar de manera natural los operadores de movimiento propuestos originalmente para el algoritmo utilizado. El rendimiento obtenido por los algoritmos es adecuado y de alta calidad

    Examination scheduling using the ant system.

    Get PDF
    This work is concerned with heuristic approaches to examination timetabling. It is demonstrated that a relatively new evolutionary method, the Ant System, can be the basis of a successful two-phase solution method. The first phase exploits ant feedback in order both to produce large volumes of feasible timetables and to optimise secondary objectives. The second phase acts as a repair facility where solution quality is improved further while maintaining feasibility. This is accomplished without increasing computational effort to unrealistic levels. The work builds on an existing implementation for the graph colouring problem, the natural model for examination scheduling. It is demonstrated that by adjusting the graph model to allow the accommodation of several side constraints as well incorporating enhancement techniques within the algorithm itself, the Ant System algorithm becomes very effective at producing feasible timetables. The enhancements include a diversification function, new reward functions and trail replenishment tactics. It is observed that the achievement of second-order objectives can be enhanced through a variety of means. A modified elitist strategy (ERF) significantly improves the performance of the Ant System due to the extra emphasis on second-order feedback. It is also shown that through the incorporation of the ERF, trail limits and, in particular, 19th century evolutionary theory the area of the solution space explored by the ants during the infancy of the search can be reduced. In addition, a good level of exploration is maintained as the search matures. This balance between exploration and exploitation is the main determinant of solution quality. The use of a repair facility, as is common practice with evolutionary algorithms, encourages fitter solutions. The interaction between Lamarckian evolution and searching in an extended neighbourhood through the graph theoretic concept of Kempe chains leads to better overall solutions

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

    Get PDF
    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

    Metaheuristics for NP-hard combinatorial optimization problems

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

    Get PDF
    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp
    corecore