This article presents an intelligent system for container stacking based on fuzzy logic. The meth... more This article presents an intelligent system for container stacking based on fuzzy logic. The method establishes a defined criterion for accepting or rejecting in real time an entry request to the stacking areas of the port in Valparaiso, Chile. A case study based on expert knowledge illustrates the proposed method with real data. First, the optimum solution is determined for a problem of maximization of entries, based on historical records from the traffic and information center of Valparaiso Port. Second, this solution is used to establish a strategy for making “the best possible decisions.” The combination of the optimization and the fuzzy results (which consider the type of cargo, prices, and capacity) is performed at two levels. First, the optimization results are used as feed for the fuzzy system to determinate a ratio of future acceptances. Second, the optimization results are compared to the fuzzy system results in order to estimate a parameter to establish the minimal percentage value for accepting a request. As a result, a proper use of the stacking area is achieved, which results in an increase of profits and revenue management.
This article presents an intelligent system for container stacking based on fuzzy logic. The meth... more This article presents an intelligent system for container stacking based on fuzzy logic. The method establishes a defined criterion for accepting or rejecting in real time an entry request to the stacking areas of the port in Valparaiso, Chile. A case study based on expert knowledge illustrates the proposed method with real data. First, the optimum solution is determined for a problem of maximization of entries, based on historical records from the traffic and information center of Valparaiso Port. Second, this solution is used to establish a strategy for making “the best possible decisions.” The combination of the optimization and the fuzzy results (which consider the type of cargo, prices, and capacity) is performed at two levels. First, the optimization results are used as feed for the fuzzy system to determinate a ratio of future acceptances. Second, the optimization results are compared to the fuzzy system results in order to estimate a parameter to establish the minimal percentage value for accepting a request. As a result, a proper use of the stacking area is achieved, which results in an increase of profits and revenue management.
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Issue 190 by Marco Mosca
accepting or rejecting in real time an entry request to the stacking areas of the port in Valparaiso, Chile. A case study based on expert
knowledge illustrates the proposed method with real data. First, the optimum solution is determined for a problem of maximization of entries,
based on historical records from the traffic and information center of Valparaiso Port. Second, this solution is used to establish a strategy for
making “the best possible decisions.” The combination of the optimization and the fuzzy results (which consider the type of cargo, prices,
and capacity) is performed at two levels. First, the optimization results are used as feed for the fuzzy system to determinate a ratio of future
acceptances. Second, the optimization results are compared to the fuzzy system results in order to estimate a parameter to establish the
minimal percentage value for accepting a request. As a result, a proper use of the stacking area is achieved, which results in an increase of
profits and revenue management.
accepting or rejecting in real time an entry request to the stacking areas of the port in Valparaiso, Chile. A case study based on expert
knowledge illustrates the proposed method with real data. First, the optimum solution is determined for a problem of maximization of entries,
based on historical records from the traffic and information center of Valparaiso Port. Second, this solution is used to establish a strategy for
making “the best possible decisions.” The combination of the optimization and the fuzzy results (which consider the type of cargo, prices,
and capacity) is performed at two levels. First, the optimization results are used as feed for the fuzzy system to determinate a ratio of future
acceptances. Second, the optimization results are compared to the fuzzy system results in order to estimate a parameter to establish the
minimal percentage value for accepting a request. As a result, a proper use of the stacking area is achieved, which results in an increase of
profits and revenue management.