A comparison of simulated annealing cooling strategies for redesigning a warehouse network problem
Simulated annealing (SA) has been a very useful stochastic method for solving problems of multidimensional global optimization that ensures convergence to a global optimum. This paper describes the use of SA for solving the warehouse redesigning network problem and compares the performance of three...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25670/ http://umpir.ump.edu.my/id/eprint/25670/ http://umpir.ump.edu.my/id/eprint/25670/1/18.1%20A%20comparison%20of%20simulated%20annealing%20cooling%20strategies.pdf |
| Summary: | Simulated annealing (SA) has been a very useful stochastic method for solving problems of multidimensional global optimization that ensures convergence to a global optimum. This paper describes the use of SA for solving the warehouse redesigning network problem and compares the performance of three different SA cooling schedules: the basic geometric cooling schedule, logarithmic and linear. Extensive computational results, which are performed and described, show that the geometric cooling schedule produces consistently better quality solutions in less time than the solutions produced by the other schemes. |
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