TY - JOUR
T1 - Multi-period maritime logistics network optimization using mixed integer programming
AU - Komarudin, null
AU - Purba, Mellianna Fiannita C.
AU - Rahman, Irvanu
N1 - Publisher Copyright:
© Int. J. of GEOMATE.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - Indonesia, as an archipelago country, is dependent to maritime logistics on transporting goods and transportation. However, its performance is still poor, indicated by high cost of logistics. Designing maritime logistics network is crucial for shipping company on developing their business. The objective of this research is to design a liner shipping logistics network on multi-period planning horizon using mixed integer programming with maximizing profit as objective function. Three given scenarios (fixed route and fleet size, fixed route but fleet size may increase, and random route and fleet size) are analyzed for ten years within three different conditions of demand (demand equals to forecasted demand, demand equals to forecasted demand of certain period, and demand is constant). The result shows that the second scenario gives the most satisfying result of objective function in profit and fleet allocation variables. The third scenario gives the highest profit on every condition and first scenario has the lowest number of vessels. The profit margin between the third and second scenario on each condition are 2.99%, 1.32%, and 0.004 % and fleet allocation gap between the first and second scenario are 1 ship, 1 ship, 0 ship respectively.
AB - Indonesia, as an archipelago country, is dependent to maritime logistics on transporting goods and transportation. However, its performance is still poor, indicated by high cost of logistics. Designing maritime logistics network is crucial for shipping company on developing their business. The objective of this research is to design a liner shipping logistics network on multi-period planning horizon using mixed integer programming with maximizing profit as objective function. Three given scenarios (fixed route and fleet size, fixed route but fleet size may increase, and random route and fleet size) are analyzed for ten years within three different conditions of demand (demand equals to forecasted demand, demand equals to forecasted demand of certain period, and demand is constant). The result shows that the second scenario gives the most satisfying result of objective function in profit and fleet allocation variables. The third scenario gives the highest profit on every condition and first scenario has the lowest number of vessels. The profit margin between the third and second scenario on each condition are 2.99%, 1.32%, and 0.004 % and fleet allocation gap between the first and second scenario are 1 ship, 1 ship, 0 ship respectively.
KW - Liner shipping
KW - Maritime logistics
KW - Mixed integer programming
KW - Multi-period
UR - http://www.scopus.com/inward/record.url?scp=85018349935&partnerID=8YFLogxK
U2 - 10.21660/2017.36.2848
DO - 10.21660/2017.36.2848
M3 - Article
AN - SCOPUS:85018349935
VL - 13
SP - 94
EP - 99
JO - International Journal of GEOMATE
JF - International Journal of GEOMATE
SN - 2186-2982
IS - 36
ER -