The United States industrial organization pattern in mixed-model-assembly-line

In modern industries, mixed-model-assembly-lines (MMAL) are widely used. There are two principal kinds of industrial organization patterns, which called the United States Pattern and the Toyota (Japan) Patter. The United States Pattern will be studied in this article and the objective of this pattern is minimizing the utility and the idle time. Genetic algorithm is been used for solving the problem and more than 5000 examples have been designed. From the results, the better parameters for the assembly line and the genetic algorithm will be known

The Japan (Toyota) industrial organization pattern in mixed-model-assembly-line

Mixed-model-assembly-lines (MMAL) are widely used in modern industries. There are two principal kinds of industrial organization patterns, which called the United States Pattern and the Japan Patter. The Japan (Toyota) Pattern will be studied in this article and the objective of this pattern is minimizing the stoppage and the idle time. Genetic algorithm is been used for solving the problem and more than 5000 examples have been designed. The results will shown the better parameters for the assembly line and the genetic algorithm

Benchmarch results of a genetic algorithm for non-permutation flowshops using constrained buffers

This paper presents the performance study of a Genetic Algorithm, for the special case of a mixed model non-permutation flowshop production line, where resequencing is permitted when stations have access to intermittent or centralized resequencing buffers. The access to the buffers is restricted by the number of available buffer places and the physical size of the products. Results from other authors are compared which presented results on permutation sequences [1] or which treat a problem similar to the one studied in this work [2], based on the benchmark data provided by Taillard [3]. Improvements that come with the introduction of constrained resequencing buffers are highlighted

Analysis and adjustment of a genetic algorithm for non-permutation flowshops

The viability of many heuristic procedures strongly depends on the adequate adjustment of parameters. This work presents an adjustment procedure which was applied to a Genetic Algorithm. First, a preliminary analysis is performed, intended to obtain a better understanding of the behavior of the parameters, as for example to estimate how likely it is for the preceding adjustment of the parameters to remain in local minima. Special attention is paid on the variability of the solutions with respect to their repeatability. The four phases of the adjustment procedure are Rough-Adjustment, Repeatability, Clustering and Fine Adjustment

Performance study of a genetic algorithm for sequencing in mixted model non-permutation flowshops using constrained buffers

This paper presents the performance study of a Genetic Algorithm applied to a mixed model non-permutation flowshop production line. Resequencing is permitted where stations have access to intermittent or centralized resequencing buffers. The access to the buffers is restricted by the number of available buffer places and the physical size of the products. Characteristics such as the difference between the intermittent and the centralized case, the number of buffer places and the distribution of the buffer places are analyzed. Improvements that come with the introduction of constrained resequencing buffers are highlighted

Extended classification for flowshops with resequencing

Este trabajo presenta una clasificación extendida de líneas de flujo no-permutación. Se consideran las múltiples opciones que se presentan al incluir la posibilidad de resecuenciar piezas en la línea. Se ha visto que en la literatura actual no se ha clasificado con profundidad este tipo de producción. Abstract This paper presents an extended cassification for non-permutation flowshops. The versatile options which occur with the possibility of resequencing jobs within the line are considered. The literature review shows that no classification exists which considers extensively this type of flowshop

Genetic algorithm for sequencing in midex model non-permutation flowshops using constrained buffers

Este trabajo presenta un Algoritmo Genético (GA) del problema de secuenciar unidades en una línea de producción. Se tiene en cuenta la posibilidad de cambiar la secuencia de piezas mediante estaciones con acceso a un almacén intermedio o centralizado. El acceso al almacén además está restringido, debido al tamaño de las piezas. Abstract This paper presents a Genetic Algorithm (GA) for the problem of sequencing in a mixed model non-permutation flowshop. Resequencing is permitted where stations have access to intermittent or centralized resequencing buffers. The access to a buffer is restricted by the number of available buffer places and the physical size of the products

Overview on: sequencing in mixed model flowshop production line with static and dynamic context

In the present work a literature overview was given on solution techniques considering basic as well as more advanced and consequently more complex arrangements of mixed model flowshops. We first analyzed the occurrence of setup time/cost; existing solution techniques are mainly focused on permutation sequences. Thereafter we discussed objectives resulting in the introduction of variety of methods allowing resequencing of jobs within the line. The possibility of resequencing within the line ranges from 1) offline or intermittent buffers, 2) parallel stations, namely flexible, hybrid or compound flowshops, 3) merging and splitting of parallel lines, 4) re-entrant flowshops, to 5) change job attributes without physically interchanging the position. In continuation the differences in the consideration of static and dynamic demand was studied. Also intermittent setups are possible, depending on the horizon and including the possibility of resequencing, four problem cases were highlighted: static, semi dynamic, nearly dynamic and dynamic case. Finally a general overview was given on existing solution methods, including exact and approximation methods. The approximation methods are furthermore divided in two cases, know as heuristics and methaheuristic

Order allocation in a multi-supplier environment: review of the literature since 2007

Purpose: Optimal order allocation on the part of the buyer in a multi-supplier environment has become a major concern in supply chains. There are numerous articles that analyze and present models for optimizing order allocation from a given panel of suppliers. The purpose of this paper is to provide an analysis on this topic which considers: (i) aims, (ii) results, (iii) model complexity, and (iv) resolution procedures. Design/methodology/approach: The paper reviews twenty-eight articles, twenty-one of them published since 2007 in journals indexed by Journal Citation Reports (in ISI Web of Knowledge) on this topic. Findings and Originality/value: This review reveals four main aspects mentioned as determinant in generating mathematical models. The analysis of these four points does not allow for a single, overarching model. Rather, all analyzed solutions reflect and respond to a specific company environment. Originality/value: A global analysis on several recent papers, describing main aspects wich determines optimal order allocation in multi-supplier environment.Peer Reviewe

Order allocation in a multi-supplier environment: review of the literature since 2007

Purpose: Optimal order allocation on the part of the buyer in a multi-supplier environment has become a major concern in supply chains. There are numerous articles that analyze and present models for optimizing order allocation from a given panel of suppliers. The purpose of this paper is to provide an analysis on this topic which considers: (i) aims, (ii) results, (iii) model complexity, and (iv) resolution procedures. Design/methodology/approach: The paper reviews twenty-eight articles, twenty-one of them published since 2007 in journals indexed by Journal Citation Reports (in ISI Web of Knowledge) on this topic. Findings: This review reveals four main aspects mentioned as determinant in generating mathematical models. The analysis of these four points does not allow for a single, overarching model. Rather, all analyzed solutions reflect and respond to a specific company environment. Originality/value: A global analysis on several recent papers, describing main aspects wich determines optimal order allocation in multi-supplier environment.Postprint (published version