Hasil Ringkasan
8 3 ( 1 * 2 3 ( 5 $ 8 1 7 8 . 0 7 5 $ 1 - 2 3 U , 1 6 * ( 0 % $ 1 $ 6 , 2 1 $ / 0 ( 1 , 1 * . 1 6 3 2 5 7 $ . D U \ D W X O L X Q W X N P H P , Q V W L W X 2 + $ 1 1 ( 1 U R J U D P 6 6 7 , 7 8 7 7 1 * $ 1 0 / SHORT . $ 7 . $ 1 $ 6 , % $ 5 $ ' , 6 ( 5 7 L V V H E D J D L V P S H U R O H K J X W 7 H N Q R O R 2 O H K ( 6 ( 6 , 0 1 , 0 6 W X G L ' R N 7 ( . 1 2 / 0 $ 5 ( 7 0 2 ' ( / 2 SEA SHI 1 . , 1 ( 5 $ 1 * 0 8 7 $ 6 , V D O D K V D W X V J H O D U ' R N W R R J L % D Q G X Q K 0 $ 1 * 8 1 N W R U 7 H N Q L / 2 * , % $ 2 3 7 , 0 $ 6 IPPING 6 5 - $ - $ 5 , 8 / 7 , 0 2 ' V \ D U D W R U G D U L Q J 1 6 2 1 * L N 6 L S L O $ 1 ' 8 1 * 6 , 6 6 6 1 * $ 1 ' $ L $ % 6 7 5 $ . 3 ( 1 * ( 0 % $ 1 * $ 1 0 2 ' ( / 2 3 7 , 0 $ 6 , 2 3 ( 5 $ 6 , 2 1 $ / SHORT SEA SHIPPING 6 6 6 8 1 7 8 . 0 ( 1 , 1 * . $ 7 . $ 1 . , 1 ( 5 - $ - $ 5 , 1 * $ 1 7 5 $ 1 6 3 2 5 7 $ 6 , % $ 5 $ 1 * 0 8 / 7 , 0 2 ' $ 2 O H K - R K D Q Q H V ( 6 L P D Q J X Q V R Q J 1 , 0 3 U R J U D P 6 W X G L ' R N W R U 7 H N Q L N 6 L S L O 6 D O D K V D W X X S D \ D X Q W X N P H P S H U E D L N L G R P L Q D Q Q \ D S H Q J J X Q D D Q P R G D G D U D W G D O D P S H U D Q J N X W D Q E D U D Q J G L , Q G R Q H V L D \ D Q J P H Q \ H E D E N D Q W L Q J J L Q \ D E L D \ D O R J L V W L N N K X V X V Q \ D E L D \ D W U D Q V S R U W D V L E D U D Q J D G D O D K G H Q J D Q P H P E H U L N D Q S H U K D W L D Q S D G D V L V W H P W U D Q V S R U W D V L E D U D Q J P X O W L P R G D 6 L V O R J Q D V P H Q \ D W D N D Q E D K Z D V D O D K V D W X S U R J U D P \ D Q J G L U H Q F D Q D N D Q X Q W X N P H Q L Q J N D W N D Q N H O D Q F D U D Q D U X V E D U D Q J G D O D P P H Q G X N X Q J H I L V L H Q V L G D Q H I H N W L I L W D V N L Q H U M D V L V W H P O R J L V W L N Q D V L R Q D O D G D O D K P H Q J H P E D Q J N D Q U X W H S H O D \ D U D Q G D Q R S H U D V L R Q D O Short Sea Shipping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bilevel programming . H S X W X V D Q S H U W D P D P H U X S D N D Q S H U P D V D O D K D Q lower level G D Q N H G X D P H U X S D N D Q S H U P D V D O D K D Q upper level 3 D G D L L lower level W H N Q L N V R O X V L R S W L P D V L \ D Q J G L J X Q D N D Q D G D O D K Increamental Assignment V H G D Q J N D Q X Q W X N upper level P H Q J J X Q D N D Q Discrete Binary Particle Swarm Optimization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moda shifting) G D U L P R G D W U X N N H P R G D 6 6 6 G D Q M X P O D K N R P E L Q D V L V N H Q D U L R R S H U D V L R Q D O \ D Q J V D Q J D W E H V D U G D S D W G L V H O H V D L N D Q G H Q J D Q W H N Q L N V R O X V L R S W L P D V L \ D Q J G L J X Q D N D Q 6 R O X V L W H U E D L N V N H Q D U L R R S H U D V L R Q D O 6 6 6 X Q W X N S H U J H U D N N D Q D Q J N X W D Q E D U D Q J 3 X O D X - D Z D ±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± 6 X P D W H U D W H U G D S D W V H E D Q \ D N N R P E L Q D V L G H Q J D Q P H Q J J X Q D N D Q W H N Q L N V R O X V L R S W L P D V L ' % 3 6 2 V R O X V L R S W L P X P M D O X U S H O D \ D U D Q 6 6 6 G D S D W G L S H U R O H K G H Q J D Q G L Z D N L O L R O H K N R P E L Q D V L D W D X G D U L W R W D O N R P E L Q D V L \ D Q J D G D : D N W X N R P S X W D V L \ D Q J G L E X W X K N D Q X Q W X N P H Q G D S D W N D Q V R O X V L R S W L P X P \ D L W X M D P M L N D G L E D Q G L Q J N D Q G H Q J D Q F D U D H Q X P H U D V L S H Q X K G L E X W X K N D Q Z D N W X M D P + D O W H U V H E X W P H Q X Q M X N N D Q E D K Z D H I H N W L Y L W D V Z D N W X N R P S X W D V L G H Q J D Q P H Q J J X Q D N D Q D O J R U L W P D ' % 3 6 2 [ O H E L K F H S D W . D W D . X Q F L W U D Q V S R U W D V L E D U D Q J P X O W L P R G D short sea shipping bilevel programming increamental assignment discrete binary particle swarm optimization L L L ABSTRACT OPTIMIZATION MODEL DEVELOPMENT FOR SHORT SEA SHIPPING (SSS) OPERATION TO IMPROVE MULTIMODAL TRANSPORTATION NETWORK PERFORMANCE By - R K D Q Q H V ( 6 L P D Q J X Q V R Q J 1 , 0 (Doctoral Program in Civil Engineering) One of efforts to improve the dominant use of land modes in Indonesia freight transportation is to intensify the multimodal freight transportation system. The dominant use of land modes leads to high logistics costs, especially the transportation cost. Sislognas 2012 states that one of the programs planned to improve the smoothness flow of goods in supporting the efficiency and effectiveness of the national logistics system performance is to develop Short Sea Shipping (SSS) shipping route and operational In the context of modeling, the design of SSS route is complex. It involves many actors and choices of operational scenarios combinations. It can be applied so that the operation of SSS has chances to be optimized. While in the context of optimization, the selection of an SSS operation scenario is a difficult combinatorial optimization problem to solve. The purpose of this study is to develop a multimodal freight transportation network model for container movements by considering SSS model and to develop an optimization model for designing operational scenarios for SSS route.. There are two main decisions to be answered simultaneously in developing the SSS route optimization model. First, it is related to network assignment which describes the behavior of the freight traffic users in choosing the travel route and mode used. Second, it is related to the selection of an optimum combination of SSS operational scenarios. It shifts land mode to the SSS mode. It is quantified by the value savings in total transportation costs that describe decision makers. The optimization approach that will be used to answer the problems above is the bilevel programming approach. The first decision is a lower-level problem and the second is an upper-level problem. The optimization solution technique for lower-level problem is Incremental Assignment, while for upper-level problem, Discrete Binary Particle Swarm Optimization (DBPSO). The operating attributes SSS are a port, SSS tariff, frequency, and SSS ship size, then the model will be tested on actual network of freight movement between Java and Sumatra. L Y The result through the operation of SSS route with some several policy scenarios is the improvement the performance of containers transportation network. It can be shown by the total savings of freight transportation costs and modal shifting from trucks to SSS. Also a great number of operational scenario combinations can be solved by the optimization solution technique used.