%0 Journal Article %1 varughese2017facility %A Varughese, Shaju %A S, Gladston Raj %D 2017 %J International Journal of Computer Science and Information Technology (IJCSIT) %K Annealing Crossover Direct Heuristic Hybrid Inbounded Logistic Mutation Search. Simulated %N 5 %P 51 - 65 %R 10.5121/ijcsit.2017.9505 %T Facility Location in Logistic Network Design Using Soft Computing Opimization Models %U http://airccse.org/journal/ijcsit2017_curr.html %V 9 %X Discovery of the optimal best possibility of location for facilities is the central problem associated in logistics management. The optimal places for the distribution centres (DCs) can be based on the selected attributes that are crucial to locate the best possible locations to increase the speed of the facility service and thus reduce the overall transport cost and time and to provide best service. The major task is to identifying and locating the required number of DCs and its optimum locations are considered as the important goals for the design of any logistics network. The number of DCs will clearly depends upon many factors like population, capacity of the facility, type of facility etc. but locating the optimum locations of DCs will reduce the overall cost. But, for solving such a wide problem space, the powerful tools are the soft computing based approaches and that are well suited and find a meaningful solution in finite time. In this work, we are going to find the optimum locations of DCs for logistics using various soft computing methods.

@article{varughese2017facility, abstract = {Discovery of the optimal best possibility of location for facilities is the central problem associated in logistics management. The optimal places for the distribution centres (DCs) can be based on the selected attributes that are crucial to locate the best possible locations to increase the speed of the facility service and thus reduce the overall transport cost and time and to provide best service. The major task is to identifying and locating the required number of DCs and its optimum locations are considered as the important goals for the design of any logistics network. The number of DCs will clearly depends upon many factors like population, capacity of the facility, type of facility etc. but locating the optimum locations of DCs will reduce the overall cost. But, for solving such a wide problem space, the powerful tools are the soft computing based approaches and that are well suited and find a meaningful solution in finite time. In this work, we are going to find the optimum locations of DCs for logistics using various soft computing methods. }, added-at = {2021-04-14T06:43:44.000+0200}, author = {Varughese, Shaju and S, Gladston Raj}, biburl = {https://www.bibsonomy.org/bibtex/2f1c74feb27b525b43e2c4e8b3ec3e74e/shamerjose}, doi = {10.5121/ijcsit.2017.9505}, interhash = {cee2002c047b053e24fe57cf37281626}, intrahash = {f1c74feb27b525b43e2c4e8b3ec3e74e}, journal = { International Journal of Computer Science and Information Technology (IJCSIT)}, keywords = {Annealing Crossover Direct Heuristic Hybrid Inbounded Logistic Mutation Search. Simulated}, month = oct, number = 5, pages = {51 - 65}, timestamp = {2021-04-14T06:43:44.000+0200}, title = {Facility Location in Logistic Network Design Using Soft Computing Opimization Models}, url = {http://airccse.org/journal/ijcsit2017_curr.html}, volume = 9, year = 2017 }