الفهرس 
The Supply Chain Network Design Problem
The Developed Mathematical ModelOnly 14 pages are availabe for public view
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Abstract
Research in the field of the multi-objective supply chain was given little
attention as compared to that given to the single objective supply chain
problems. In addition, most of researches, which tackle the multi-objective
problems, aim at finding either one non-dominated solution for dynamic
problem or Pareto front for static problem. Little attention has been given
to consider the role of dynamic location allocation on designing supply
chain.
In the present work multi-objective four echelons single product supply
chain network design in dynamic environment is considered. The network
under study consists of suppliers, plants distributors and customers
echelons. This problem is concerned with finding the Pareto front includes
different SeNDs with trade-off between two objectives. These objectives
are minimizing the total cost and maximizing the service level. At each
solution two decisions are taken. These decisions are locating plants and
distributers in any period when they are needed and allocating quantities
between each two successive echelons.
A Genetic Algorithm is developed to solve this problem. The developed
algorithm applies a new chromosome representation with its decodingencoding
procedures to effectively tackle the multi-objective supply chain
with dynamic nature.
The model has successfully tackled the multi-objective supply chain
network design problem with dynamic location allocation. The results are
more practical as it considers the Pareto front for minimizing the total cost
and maximizing the service level, other than optimizing only one of these
objectives. The results proved that considering different capacities for the
potential plants and distributors is better than similar capacity as it leads to
less total cost. The dynamic location allocation approach proved to be superior to the static location dynamic allocation approach in increasing
and product life cycle demand patterns, while in decreasing and constant
demand patterns are approximately the same.