113 research outputs found

    Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines

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    Copyright © 2015 Springer. This is a PDF file of an unedited manuscript that has been accepted for publication in The International Journal of Advanced Manufacturing Technology. The final publication is available at: http://link.springer.com/article/10.1007/s00170-015-7320-y. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Different from a large number of existing studies in the literature, this paper addresses two important issues in managing production lines, the problems of line balancing and model sequencing, concurrently. A novel hybrid agent-based ant colony optimization–genetic algorithm approach is developed for the solution of mixed model parallel two-sided assembly line balancing and sequencing problem. The existing agent-based ant colony optimization algorithm is enhanced with the integration of a new genetic algorithm-based model sequencing mechanism. The algorithm provides ants the opportunity of selecting a random behavior among ten heuristics commonly used in the line balancing domain. A numerical example is given to illustrate the solution building procedure of the algorithm and the evolution of the chromosomes. The performance of the developed algorithm is also assessed through test problems and analysis of their solutions through a statistical test, namely paired sample t test. In accordance with the test results, it is statistically proven that the integrated genetic algorithm-based model sequencing engine helps agent-based ant colony optimization algorithm robustly find significantly better quality solutions

    A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Typically, the total number of required workstations are minimised for a given cycle time (this problem is referred to as type-1), or cycle time is minimised for a given number of workstations (this problem is referred to as type-2) in traditional balancing of assembly lines. However, variation in workload distributions of workstations is an important indicator of the quality of the obtained line balance. This needs to be taken into account to improve the reliability of an assembly line against unforeseeable circumstances, such as breakdowns or other failures. For this aim, a new problem, called lexicographic bottleneck mixed-model assembly line balancing problem (LB-MALBP), is presented and formalised. The lexicographic bottleneck objective, which was recently proposed for the simple single-model assembly line system in the literature, is considered for a mixed-model assembly line system. The mathematical model of the LB-MALBP is developed for the first time in the literature and coded in GAMS solver, and optimal solutions are presented for some small scale test problems available in the literature. As it is not possible to get optimal solutions for the large-scale instances, an artificial bee colony algorithm is also implemented for the solution of the LB-MALBP. The solution procedures of the algorithm are explored illustratively. The performance of the algorithm is also assessed using derived well-known test problems in this domain and promising results are observed in reasonable CPU times

    Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Assembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., cars, buses, trucks). Locating two lines in parallel helps improve line efficiency by enabling collaboration between the line workers. This paper proposes a mixed-model parallel two-sided assembly line system that can be utilized to produce large-sized items in an inter-mixed sequence. The mixed-model parallel two-sided line balancing problem is defined and the advantages of utilizing multi-line stations across the lines are discussed. A flexible agent-based ant colony optimization algorithm is developed to solve the problem and a numerical example is given to explain the method systematically. The proposed algorithm builds flexible balancing solutions suitable for any model sequence launched. The dynamically changing workloads of workstations (based on specific product models during the production process) are also explored. A comprehensive experimental study is conducted and the results are statistically analyzed using the well-known paired sample t-test. The test results indicate that the mixed-model parallel two-sided assembly line system reduces the workforce need in comparison with separately balanced mixed-model two-sided lines. It is also shown that the proposed algorithm outperforms the tabu search algorithm and six heuristics often used in the assembly line balancing domain

    Type-E Parallel Two-Sided Assembly Line Balancing Problem: Mathematical Model and Ant Colony Optimisation based Approach with Optimised Parameters

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    Copyright © 2015 Elsevier. This is a PDF file of an unedited manuscript that has been accepted for publication in Computers and Industrial Engineering (doi:10.1016/j.cie.2014.12.037). The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.There are many factors which affect the performance of a complex production system. Efficiency of an assembly line is one of the most important of these factors since assembly lines are generally constructed as the last stage of an entire production system. Parallel two-sided assembly line system is a new research domain in academia though these lines have been utilised to produce large sized products such as automobiles, trucks, and buses in industry for many years. Parallel two-sided assembly lines carry practical advantages of both parallel assembly lines and two-sided assembly lines. The main purpose of this paper is to introduce type-E parallel two-sided assembly line balancing problem for the first time in the literature and to propose a new ant colony optimisation based approach for solving the problem. Different from the existing studies on parallel assembly line balancing problems in the literature, this paper aims to minimise two conflicting objectives, namely cycle time and number of workstations at the same time and proposes a mathematical model for the formal description of the problem. To the best of our knowledge, this is the first study which addresses both conflicting objectives on a parallel two-sided assembly line configuration. The developed ant colony optimisation algorithm is illustrated with an example to explain its procedures. An experimental design is also conducted to calibrate the parameters of the proposed algorithm using response surface methodology. Results obtained from the performed computational study indicate that minimising cycle time as well as number of workstations help increase system efficiency. It is also observed that the proposed algorithm finds promising results for the studied cases of type-E parallel two-sided assembly line balancing problem when the results are compared with those obtained from other three well-known heuristics

    Image Edge Feature Extraction and Refining Based on Genetic-Ant Colony Algorithm

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    Edge is composed by a collection of its nearby pixels which has a step change or changes in roof, an image is an information system and most of its information comes from the edges. This paper gives a brief overview of the status and the importance of image edge detection and introduces the research status of the image edge detection. After that, it introduces the basic principle and the main steps of the genetic algorithm and ant colony algorithm. On the basis of these, the paper proposed a new hybrid algorithm for the image edge extraction and refining, which combined the genetic algorithm and ant colony algorithm. Through the analysis of the time-speed graph of the genetic algorithm and the ant colony algorithm, we can find the best fusion point between the genetic algorithm and the ant colony algorithm. The experiment indicated the proposed hybrid algorithm can make the full use of the image information, the simulation time is shorter, the image edge is more continuous, and preserved the outline of original image more completely

    Mixed-model Sequencing with Stochastic Failures: A Case Study for Automobile Industry

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    In the automotive industry, the sequence of vehicles to be produced is determined ahead of the production day. However, there are some vehicles, failed vehicles, that cannot be produced due to some reasons such as material shortage or paint failure. These vehicles are pulled out of the sequence, and the vehicles in the succeeding positions are moved forward, potentially resulting in challenges for logistics or other scheduling concerns. This paper proposes a two-stage stochastic program for the mixed-model sequencing (MMS) problem with stochastic product failures, and provides improvements to the second-stage problem. To tackle the exponential number of scenarios, we employ the sample average approximation approach and two solution methodologies. On one hand, we develop an L-shaped decomposition-based algorithm, where the computational experiments show its superiority over solving the deterministic equivalent formulation with an off-the-shelf solver. Moreover, we provide a tabu search algorithm in addition to a greedy heuristic to tackle case study instances inspired by our car manufacturer partner. Numerical experiments show that the proposed solution methodologies generate high quality solutions by utilizing a sample of scenarios. Particularly, a robust sequence that is generated by considering car failures can decrease the expected work overload by more than 20\% for both small- and large-sized instances.Comment: 30 pages, 9 figure

    Tabu Search Algorithm for Single and Multi-model Line Balancing Problems

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    This paper deals with the assembly line balancing issue. The considered objective is to minimize the weighted sum of products’ cycle times. The originality of this objective is that it is the generalization of the cycle time minimization used in single-model lines (SALBP) to the multi-model case (MALBP). An optimization algorithm made of a heuristic and a tabu-search method is presented and evaluated through an experimental study carried out on several and various randomly generated instances for both the single and multiproduct cases. The returned solutions are compared to optimal solutions given by a mathematical model from the literature and to a proposed lower bound inspired from the classical SALBP bound. The results show that the algorithm is high performing as the average relative gap between them is quite low for both problems

    Research Article Balancing the Production Line by the Simulation and Statistics Techniques: A Case Study

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    Abstract: A wide range of the real world problems in industries are related to misbalances of the production line and excessive Work in Process parts (WIP). Simulation is an effective method to recognize these problems with consuming least cost and time. Moreover, total system efficiency of a production line can be extremely improved by examining different solution scenario via the simulation techniques. In this research, we utilize the simulation technique founded upon the software Enterprise Dynamics (ED) for evaluating the cause of these problems and trying to find the improvement solutions in Sadid Pipe and Equipment Company (SPECO). Two parameters of diameter and thickness are important factors affecting the time of workstations. The effects of these factors on process time are evaluated by hypothesis tests. Two improvement scenarios have been presented. In the first scenario, the layout design of the factory has been improved with regard to production process and bottleneck station. In the second one, an essential improvement has been carried out by reduction in wastages. Regarding the accomplished simulations, it is concluded that it is possible to eliminate the existing bottleneck by implementing changes in the locations of production stations or reducing the waste in some stations. The improvements eventually result in balancing the production line

    Horizontal balancing for mixed models assembly lines

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    Traditionally assembly lines have been used to produce high volumes of a single model. To take advantage of these lines in flexible manufacturing environments, we can implement mixed model lines which allow ma­nufacturing different products of a family in the same line, however, its balancing requires different techniques that traditional. In this research, a literature review was made to analyze the factors affecting the mixed model lines in MTO environments and based on this we developed a mathematical optimization model to stabilize workloads making easier the decision about production sequences that are programmed on the line. The model was run in several instances and the results were significantly better than those obtained with a line balancing traditional method.Las líneas de ensamble tradicionalmente han sido utilizadas para producir grandes cantidades de un único modelo. Para aprovechar las ventajas de estas en ambientes de manufactura flexibles, se pueden implementar líneas de modelos mixtos las cuales permiten ensamblar diferentes productos de una familia en una misma línea; sin embargo, su balanceo requiere técnicas diferentes de las tradicionales. En esta investigación se hizo una revisión bibliográfica para analizar los factores que afectan las líneas de modelos mixtos y con base en esto se desarrolló un modelo de optimización ma­temática que estabiliza las cargas de trabajo, facilitando la decisión sobre las secuencias de producción que se programan en la línea. El modelo se corrió en varios escenarios y se obtuvieron resultados significativamente mejores que los obtenidos con un método tradicional de balance
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