An integer programming approach for Balancing and Scheduling in Extended Manufacturing Environment

In the fiercely competitive era induced by expansion of open business archetypes, the managerial aspects of Extended Manufacturing Environments (EMEs) are experiencing growing concerns. There is no scope of leaving a possible operational improvement unexplored. For enhanced operational efficiency and capacity utilization the balancing and scheduling problems of EMEs are, therefore, rightfully considered and an integer programme is proposed in this paper. The model is designed in a spread sheet and solved through What'sBest optimizer. The model capabilities is assessed through a test problem. The results have demonstrated that the model is capable of defining optimized production schedules for EMEs.This study has been conducted under FRGS project (FRGS14- 102-0343) funded by Ministry of Higher Education (MOHE), Malaysia. The authors are grateful to MOHE and Research Management Centre (RMC), International Islamic University Malaysia (IIUM) for their support.info:eu-repo/semantics/publishedVersio

A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm. This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorith

A Lagrangean relaxation approach for the mixed-model flow line sequencing problem.

In this study, a mixed-model flow line sequencing problem is considered. A mixed-model flow line is a special case of production line where products are transported on a conveyor belt, and different models of the same product are intermixed on the same line. We have focused on product-fixed, rate-synchronous lines with variable launching. Our objective function is minimizing makespan. A heuristic algorithm based on Lagrangean relaxation is developed for the problem, and tested in terms of solution quality and computational efficiency

Equilibrado de líneas de montaje de productos voluminosos

Preprin

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, DOI: 10.1016/j.ijpe.2014.08.010One of the key factors of a successfully implemented mixed-model line system is considering model sequencing problem as well as the line balancing problem. In the literature, there are many studies, which consider these two tightly interrelated problems individually. However, we integrate the model sequencing problem in the line balancing procedure to obtain a more efficient solution for the problem of Simultaneous Balancing and Sequencing of Mixed-Model Parallel Two-Sided Assembly Lines. A mathematical model is developed to present the problem and a novel agent based ant colony optimisation approach is proposed as the solution method. Different agents interact with each other to find a near optimal solution for the problem. Each ant selects a random behaviour from a predefined list of heuristics and builds a solution using this behaviour as a local search rule along with the pheromone value. Different cycle times are allowed for different two-sided lines located in parallel to each other and this yields a complex problem where different production cycles need to be considered to build a feasible solution. The performance of the proposed approach is tested through a set of test cases. Experimental results indicate that considering model sequencing problem with the line balancing problem together helps minimise line length and total number of required workstations. Also, it is found that the proposed approach outperforms other three heuristics tested

ASALBP: the Alternative Subgraphs Assembly Line Balancing Problem. Formalization and Resolution Procedures

Hoy en día, los problemas de equilibrado de líneas de montaje se encuentran comúnmente en la mayoría de sistemas industriales y de manufactura. Básicamente, estos problemas consisten en asignar un conjunto de tareas a una secuencia ordenada de estaciones de trabajo, de manera que se respeten las restricciones de precedencia y se optimice una medida de eficiencia dada (como, por ejemplo, el número de estaciones de trabajo o el tiempo ciclo). Dada la complejidad de los problemas de equilibrado de líneas, en los trabajos de investigación tradicionalmente se consideraban numerosas simplificaciones en las que, por ejemplo, una sola línea serial procesaba un único modelo de un solo producto. Además, los problemas estaban principalmente restringidos por las relaciones de precedencia y el tiempo ciclo. Sin embargo, la disponibilidad de recursos computacionales de hoy en día, así como la necesidad de las empresas a adaptarse a los rápidos cambios en los procesos de producción, han motivado tanto a investigadores como a gerentes a tratar problemas más realistas. Algunos ejemplos incluyen problemas que procesan modelos mixtos, estaciones de trabajo y líneas en paralelo, consideran múltiples objetivos y restricciones adicionales, como la capacidad de proceso de las estaciones de trabajo y la ubicación de los recursos en la línea de montaje.Esta tesis doctoral trata un nuevo problema de equilibrado de líneas, que ha sido titulado ASALBP: the Alternative Subgraphs Assembly Line Balancing Problem, en el que se consideran variantes alternativas para diferentes partes de un proceso de montaje o de manufactura. Cada alternativa puede ser representada por un subgrafo de precedencias, que determina las tareas requeridas para procesar un producto particular, las restricciones de precedencia y los tiempos de proceso. Para resolver eficientemente el ASALBP, se deben resolver dos problemas simultáneamente: (1) el problema de decisión para seleccionar un subgrafo de montaje para cada parte que admite alternativas y (2) el problema de equilibrado para asignar las tareas a las estaciones de trabajo. El análisis del estado del arte revela que este problema no ha sido estudiado previamente en la literatura, lo que ha conducido a la caracterización y a la definición de un nuevo problema. Por otra parte, dado que no es posible representar las variantes de montaje en un diagrama de precedencias estándar, se propone el S-grafo como una herramienta de diagramación, para representar en un único grafo todas las alternativas de montaje.Habitualmente, los problemas de equilibrado de líneas que consideran alternativas de montaje se resuelven en dos etapas. En la etapa inicial, el diseñador de sistema selecciona una de las variantes posibles utilizando cierto criterio de decisión como por ejemplo tiempo total de proceso. Una vez que se han seleccionado las alternativas de montaje, y se dispone de un diagrama de precedencias (es decir, el problema de planificación ha sido resuelto), la línea de montaje es equilibrada en una segunda etapa. Sin embargo, utilizando dicho procedimiento de dos etapas no se puede garantizar que una solución óptima del problema global se pueda obtener, porque las decisiones tomadas por el diseñador de sistema restringen el problema y causan perdida de información; es decir, cuando se selecciona una alternativa priori los efectos de las posibilidades restantes quedan sin explorar. Por ejemplo, si el diseñador de sistema utiliza tiempo total de proceso como criterio de decisión, la alternativa con el tiempo total de proceso más grande será descartada a pesar de que pueda ser la que proporcione la mejor solución del problema (es decir, requiere el mínimo número de estaciones de trabajo o el mínimo tiempo ciclo). Por lo tanto, pareciera razonable considerar que para solucionar eficientemente un ALBP que implica alternativas de proceso, todas las alternativas de montaje deben ser tomadas en cuenta en el proceso de equilibrado. Para este propósito, en esta tesis el problema de selección de una variante de montaje y el problema de equilibrado de la línea se consideran conjuntamente en lugar de independientemente.Para resolver el Problema de Equilibrado de Líneas con Alternativas de Montaje (ASALBP) se usan varios enfoques. El problema se formaliza y se resuelve de manera óptima a través de dos modelos de programación matemática. Un enfoque aproximativo es usado para resolver problemas de tamaño industrial. Además, se proponen procedimientos de optimización local con el objetivo de mejorar la calidad de las soluciones obtenidas por los métodos heurísticos desarrollados en este trabajo.Nowadays assembly line balancing problems are commonly found in most industrial and manufacturing systems. Basically, these problems seek to assign a set of assembly tasks to an ordered sequence of workstations in such a way that precedence constraints are maintained and a given efficiency measure (e.g. the number of workstations or the cycle time) is optimized.Because of the computational complexity of balancing problems, research works traditionally considered numerous simplifying assumptions in which, for example, a single model of a unique product were processed in a single line; moreover, problems were mainly restricted by precedence and cycle time constrains. Nevertheless, the current availability of computing resources and the enterprises need to adapt to rapid changes in production and manufacturing processes have encouraged researchers and decision-makers to address more realistic problems. Some examples include problems that involve mixed models, parallel workstations and parallel lines, multiple objectives and also further restrictions such as workstation processing capacity and resource allocation constraints. This doctoral thesis addresses a novel assembly line balancing problem, entitled here ASALBP: the Alternative Subgraphs Assembly Line Balancing Problem, which considers alternative variants for different parts of an assembly or manufacturing process. Each variant can be represented by a precedence subgraph that establishes the tasks required to process a particular product, their precedence requirements and their processing times. Therefore, to efficiently solve the Alternative Subgraphs Assembly Line Balancing Problem two subproblems need to be solved simultaneously: (1) the decision problem that selects one assembly variant for each part that admit alternatives and (2) the balancing problem that assigns the tasks to the workstations. The analysis of the state-of-the-art carried out revealed that the Alternative Subgraphs Assembly Line Balancing Problem has not been addressed before in literature studies, which leaded to the characterization and definition of this new problem. Moreover, due to the impossibility of representing assembly variants in a standard precedence graph, the S-Graph is proposed here as a diagramming tool to represent all available assembly alternatives in a unique diagram. Habitually, problems involving assembly alternatives are solved by using a two-stage based approach. In the initial stage, the system designer selects one of the possible variants according to criteria such as total processing time. Once the assembly alternatives have been selected, and a precedence graph is available (i.e. the assembly planning problem has been already solved), the line is then balanced in the second stage. However, by following this two-stage procedure it cannot be guaranteed that an optimal solution of the global problem can be obtained, because the decisions taken by the system designer restrict the problem and cause information loss; i.e., a priori selection of an alternative leaves the effects of the other possibilities unexplored. For instance, if the system designer uses total processing time as decision criterion, the alternative with largest total processing time will be discarded notwithstanding it may provide the best solution of the problem (i.e., it requires the minimum number of workstations or minimum cycle time). Therefore, it seems reasonable to consider that to solve efficiently an ALBP that involves processing alternatives all possibilities must be considered within the balancing process. For this purpose, in this thesis both the variant selection problem and the balancing problem are jointly considered instead of independently.Different approaches are used here to address the Alternative Subgraphs Assembly Line Balancing Problem (ASALBP). The problem is formalize and optimally solved by means of two mathematical programming models. An approximate approach is used to address industrial-scale problems. Furthermore, local optimization procedures are proposed aiming at improving the quality of the solutions provided by all heuristic methods developed here

AWALBP-L2 : the Accessibility Windows Assembly Line Balancing Problem Level 2 : formalization and solution methods

This doctoral thesis tackles an assembly line balancing problem with restricted access to the workpieces that has been entitled AWALBP: the Accessibility Windows Assembly Line Balancing Problem. The problem is described and a general classification for its main optimization levels is proposed. The thesis focuses on a specific case of the optimization level AWALBP-L2. The AWALBP-L2 consists of two subproblems that need to be solved simultaneously: (i) the computation of a feasible movement scheme and (ii) the assignment of each task to one workstation and one stationary stage of the cycle. In the particular case of AWALBP-L2 addressed in this thesis, for each task a single workstation is compatible. The review of the state of the art reveals that relatively few studies have been published concerning the AWALBP. Regarding the solution of the AWALBP-L2, the only available previous work is a mathematical programming model, but the model is not tested or validated. In order to fill this research gap, the aim of this thesis is three-fold: i) to describe the AWALBP and characterize its main optimization levels, ii) to propose exact methods for the case of AWALBP-L2 considered, and iii) to develop solution procedures for the challenging instances that are out of reach of the former methods. Consequently, in this doctoral thesis the AWALBP is characterized and the AWALBP-L2 case is addressed through four main approaches. First, the problem is formalized and solved via two mixed integer linear programming (MILP) models. Second, an approach combining a matheuristic and a MILP model is proposed. The third approach considers hybridizing metaheuristics with mathematical programming models. Finally, the fourth approach proposes sequential combinations of the aforementioned hybrid metaheuristics and a MILP model. The performance of all approaches is evaluated via an extensive computational experiment based on realistic instances, and an optimal solution could be found for a large number of them. Future research work may include additional assumptions on the problem, such as precedence relationships among tasks or several workstations compatible for each task. The methods proposed in this thesis are open in nature and extend perspectives for combining (meta)heuristics and mathematical programming models, either for improving the solution of the AWALBP-L2 or for tackling other combinatorial optimization problems.Esta tesis doctoral aborda un problema de equilibrado de líneas con acceso limitado a las piezas que ha sido titulado AWALBP: Accessibility Windows Assembly Line Balancing Problem. Se describe el problema y se propone una clasificación general de sus principales niveles de optimización. La tesis se centra en un caso específico del nivel AWALBP-L2. El AWALBP-L2 consta de dos subproblemas que deben ser resueltos simultáneamente: (i) cálculo de un esquema de movimiento factible y (ii) asignación de cada tarea a una estación y a una de las etapas estacionarias del ciclo. En el caso particular de AWALBP-L2 tratado en esta tesis, para cada tarea existe una única estación compatible. La revisión del estado del arte revela que relativamente pocos estudios han sido publicados sobre el AWALBP. Respecto a la resolución del AWALBP-L2, el único trabajo anterior disponible es un modelo de programación matemática, el cual no está probado o validado. Con tal de cubrir este hueco de investigación, el objetivo de la presente tesis es triple: i) describir el AWALBP y caracterizar sus principales niveles de optimización, ii) proponer métodos exactos para el caso considerado de AWALBP-L2, y iii) desarrollar métodos de resolución para los ejemplares más difíciles que quedaron fuera del alcance de los métodos anteriores. Por consiguiente, en esta tesis doctoral se caracteriza el AWALBP y se aborda el caso de AWALBP-L2 mediante cuatro enfoques principales. En primer lugar, el problema se formaliza y se resuelve mediante dos modelos de programación lineal entera mixta (PLEM). En segundo lugar se propone una mateheurística combinada con un modelo de PLEM. El tercer enfoque consiste en hibridizar metaheurísticas con modelos de programación matemática. Finalmente, el cuarto enfoque propone combinaciones secuenciales de las mencionadas metaheurísticas híbridas con un modelo de PLEM. Los enfoques propuestos se evalúan mediante una extensa experiencia computacional con ejemplares realistas, y se obtuvo una solución óptima para un gran número de ellos. Las líneas propuestas de investigación futura incluyen supuestos adicionales tales como relaciones de precedencia entre tareas o varias estaciones compatibles para una misma tarea. Los métodos propuestos en esta tesis son de naturaleza abierta y ofrecen perspectivas para la combinación de (meta)heurísticas con modelos de programación matemática, tanto para mejorar la solución del AWALBP-L2 como para abordar otros problemas de optimización combinatoria

Modelling and Solving Mixed-model Parallel Two-sided Assembly Line Problems

The global competitive environment and the growing demand for personalised products have increased the interest of companies in producing similar product models on the same assembly line. Companies are forced to make significant structural changes to rapidly respond to diversified demands and convert their existing single-model lines into mixed-model lines in order to avoid unnecessary new line construction cost for each new product model. Mixed-model assembly lines play a key role in increasing productivity without compromising quality for manufacturing enterprises. The literature is extensive on assembling small-sized products in an intermixed sequence and assembling large-sized products in large volumes on single-model lines. However, a mixed-model parallel two-sided line system, where two or more similar products or similar models of a large-sized product are assembled on each of the parallel two-sided lines in an intermixed sequence, has not been of interest to academia so far. Moreover, taking model sequencing problem into consideration on a mixed-model parallel two-sided line system is a novel research topic in this domain. Within this context, the problem of simultaneous balancing and sequencing of mixed-model parallel two-sided lines is defined and described using illustrative examples for the first time in the literature. The mathematical model of the problem is also developed to exhibit the main characteristics of the problem and to explore the logic underlying the algorithms developed. The benefits of utilising multi-line stations between two adjacent lines are discussed and numerical examples are provided. An agent-based ant colony optimisation algorithm (called ABACO) is developed to obtain a generic solution that conforms to any model sequence and it is enhanced step-by-step to increase the quality of the solutions obtained. Then, the algorithm is modified with the integration of a model sequencing procedure (where the modified version is called ABACO/S) to balance lines by tracking the product model changes on each workstation in a complex production environment where each of the parallel lines may a have different cycle time. Finally, a genetic algorithm based model sequencing mechanism is integrated to the algorithm to increase the robustness of the obtained solutions. Computational tests are performed using test cases to observe the performances of the developed algorithms. Statistical tests are conducted through obtained results and test results establish that balancing mixed-model parallel two-sided lines together has a significant effect on the sought performance measures (a weighted summation of line length and the number of workstations) in comparison with balancing those lines separately. Another important finding of the research is that considering model sequencing problem along with the line balancing problem helps algorithm find better line balances with better performance measures. The results also indicate that the developed ABACO and ABACO/S algorithms outperform other test heuristics commonly used in the literature in solving various line balancing problems; and integrating a genetic algorithm based model sequencing mechanism into ABACO/S helps the algorithm find better solutions with less amount of computational effort