Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Green Logistics becomes critical in Supply Chain Management due to it having less of an impact to the environment. Green Logistics optimization refers to the determination depot quantity, decreasing uncovered demand and CO2 emission reduction. To date, application of Cuckoo searching algorithm has...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/14864/1/P002%20pg10-21.pdf http://umpir.ump.edu.my/id/eprint/14864/ http://ee.ump.edu.my/ncon/ |
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| Summary: | Green Logistics becomes critical in Supply Chain Management due to it having less of an impact to the environment.
Green Logistics optimization refers to the determination depot quantity, decreasing uncovered demand and CO2 emission reduction. To date, application of Cuckoo searching algorithm has been proven to be very efficient and reliable in solving optimization problems; it is also capable of operating simultaneously with multiple solutions. Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. In this paper, a modified Cuckoo searching
algorithm is proposed to solve the multiple objective Green Logistics optimization problem. MATLAB software is used to
validate and evaluate the proposed model. This work forms the basis for solving many other similar problems that occur in manufacturing and service industries. The final solution to this multiple objective problem is reached by using a set of Pareto solutions. |
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