Linear programming embedded particle swarm optimization for solving an extended model of dynamic virtual cellular manufacturing systems

 

H. Rezazadeh*¹, M. Ghazanfari², S. J. Sadjadi³, Mir.B. Aryanezhad⁴, A. Makui⁵

 

^1,2,3,4,5 Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran, Tel.: 0098–914–4027521; Fax: 0098–171–2240855; *E–mail: Hassan.Rezazadeh@gmail.com; h–rezazadeh@tabrizu.ac.ir

 

ABSTRACT

The concept of virtual cellular manufacturing system (VCMS) is finding acceptance among researchers as an extension to group technology. In fact, in order to realize benefits of cellular manufacturing system in the functional layout, the VCMS creates provisional groups of resources (machines, parts and workers) in the production planning and control system. This paper develops a mathematical model to design the VCMS under a dynamic environment with a more integrated approach where production planning, system reconfiguration and workforce requirements decisions are incorporated. The advantages of the proposed model are as follows: considering the operations sequence, alternative process plans for part types, machine time–capacity, worker time–capacity, cross–training, lot splitting, maximal cell size, balanced workload for cells and workers. An efficient linear programming embedded particle swarm optimization algorithm is used to solve the proposed model. The algorithm searches over the 0–1 integer variables and for each 0–1 integer solution visited; corresponding values of integer variables are determined by solving a linear programming sub–problem using the simplex algorithm. Numerical examples show that the proposed method is efficient and effective in searching for near optimal solutions.

Keywords: Dynamic virtual cellular manufacturing system; production plannig; particle swarm optimization; linear programming.

 

RESUMEN

El concepto de sistema de manufactura celular virtual (SMCV) está siendo aceptado entre los investigadores como una extensión de la tecnología de grupos. De hecho, para hacer realidad los beneficios del sistema de manufactura celular en el diseño funcional, el SMCV crea grupos provisionales de recursos (máquinas, partes y trabajadores) en la planificación de la producción y el sistema de control. En el presente trabajo se describe el desarrollo de un modelo matemático para diseñar el SMCV en el marco de un entorno dinámico con un enfoque más integrado en donde se incorporan la planificación de la producción, la reconfiguración del sistema y las decisiones relacionadas con los requisitos de la fuerza de trabajo. Las ventajas del modelo propuesto son las siguientes: considera la secuencia de operaciones, planes de proceso alternativos según los tipos de partes, tiempo de trabajo de la máquina, tiempo de trabajo del trabajador, capacitación mixta, división del trabajo, tamaño máximo de la célula y carga de trabajo balanceada para las células y trabajadores. Para resolver el modelo propuesto se usa un algoritmo eficiente de optimización por enjambre de partículas embebidas de programación lineal. El algoritmo busca en las variables enteras 0–1 y cada variable entera 0–1 visitada; los valores correspondientes de las variables enteras se determinan resolviendo una parte de un problema de programación lineal por medio del algoritmo simple. Mediante ejemplos numéricos se demuestra que el método propuesto es eficiente y efectivo en la búsqueda de soluciones casi óptimas.

 

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