چکیده:
Optimization of the complete manufacturing and supply process has become a
critical ingredient for gaining a competitive advantage. This article provides a
unified mathematical framework for modeling manufacturing cell configuration and
raw material supplier selection in a two-level supply chain network. The commonly
used manufacturing design parameters along with supplier selection and a
subcontracting approach are incorporated into our mathematical model. To the
authors’ knowledge, there is no single model which integrates all of these attributes
simultaneously. A sensitivity analysis is also performed to study the effects of this
integration. An efficient meta-heuristic based on Genetic Algorithm (GA) search
procedure is employed to effectively solve the model in medium and large scales.
We improve the GA search mechanism by proper combination of linear
programming optimization technique and GA in a cooperative framework.
Computational results show that our hybrid solution technique can find satisfactory
solutions in a timely manner
خلاصه ماشینی:
"Successful integration of CMS design and supplier selection related issues addresses the cell formation to obtain optimal or effective solutions in view of corporate overall operation.
In this article, we develop a scheme for hybridizing an exact method based on Linear Programming (LP) with a nature-inspired meta-heuristic, Genetic Algorithm (GA), for solving the integrated cell formation and supplier selection problem.
In the presented paper, a unified mathematical model for integrating manufacturing cell configuration and raw material supplier selection in a two-level Supply Chain (SC) network with an extensive coverage of important design attributes is presented.
Zopmc 1, if oth operation of part p can be processed on machine m (View the image of this page)he objective function given in Equation (1) seeks to minimize machine acquisition cost, machine operating cost, intercellular movements cost, intracellular material handling cost, final product subcontracting cost, component supplier selection fixed cost, component procurement cost, component quality deficiency penalty cost, and component lead time delay penalty cost, respectively.
Moreover, the detailed description of the main components for implementing LP embedded GA, as a solution approach to the integrated cell formation and supplier selection problem, is proposed in the following.
(View the image of this page)This paper contributes to the literature by incorporating various manufacturing design attributes such as alternative process routings, operation sequences, part demands, processing times, machine capacity, machine duplication, etcetera along with supplier selection and a subcontracting approach."