5. Conclusions
In this study a SN problem is modeled with consideration of warehousing and transportation functions. A
holonic approach, which has been found to be a general application area in manufacturing systems, is adapted
to the SN problem. Here we attempt to prove that holonic approach can be used in various problems areas,
like physical flow of goods in SN, by setting off from the autonomy and cooperativeness which are generic
concepts. The objectives of these autonomous functional entities and the overall objective of the SN are
brought together in one objective function. By considering the constraints related with supplier and warehouse
capacities, starting inventory and delayed product levels, transportation times, manufacturer demands, etc.,
the linear programming model has solved via GAMS package program. The model results were compared
for different scenarios. Then sensitivity analyses are realized to measure the sensitivity of the model results
for different parameter values.
In this paper we constituted a small sized model in terms of decision variables and constraints. This twoechelon
SN model will be expanded when it is required to apply for wider SN problems. In that case the number
of warehousing points will increase and new trade-offs will be faced. Another issue is considering alternative
transportation modes between echelons for each point pairs. In that situation new decision
variables emerges and the model complexity increases. It is obvious that managing the SNs is a comprehensive
topic and there are additional variables and parameters which can be embedded to the model. As an
example, a vehicle routing problem can also be added to the model to determine the number of carriers or
their capacities that will realize the transportation between echelons. This type of large sized models is
NP-complete. However, approximate results can easily be obtained for complex problems by using various
simulation techniques or heuristics, such as, simulated annealing, tabu search, genetic algorithms etc.
5. ConclusionsIn this study a SN problem is modeled with consideration of warehousing and transportation functions. Aholonic approach, which has been found to be a general application area in manufacturing systems, is adaptedto the SN problem. Here we attempt to prove that holonic approach can be used in various problems areas,like physical flow of goods in SN, by setting off from the autonomy and cooperativeness which are genericconcepts. The objectives of these autonomous functional entities and the overall objective of the SN arebrought together in one objective function. By considering the constraints related with supplier and warehousecapacities, starting inventory and delayed product levels, transportation times, manufacturer demands, etc.,the linear programming model has solved via GAMS package program. The model results were comparedfor different scenarios. Then sensitivity analyses are realized to measure the sensitivity of the model resultsfor different parameter values.In this paper we constituted a small sized model in terms of decision variables and constraints. This twoechelonSN model will be expanded when it is required to apply for wider SN problems. In that case the numberof warehousing points will increase and new trade-offs will be faced. Another issue is considering alternativetransportation modes between echelons for each point pairs. In that situation new decisionvariables emerges and the model complexity increases. It is obvious that managing the SNs is a comprehensive
topic and there are additional variables and parameters which can be embedded to the model. As an
example, a vehicle routing problem can also be added to the model to determine the number of carriers or
their capacities that will realize the transportation between echelons. This type of large sized models is
NP-complete. However, approximate results can easily be obtained for complex problems by using various
simulation techniques or heuristics, such as, simulated annealing, tabu search, genetic algorithms etc.
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