THE DEVELOPMENT OF CITY LOGISTICS MODEL FOR MEGACITY (CASE STUDY: DKI JAKARTA)

• Main Author: INDAH SARAGIH NIM 33412004, NOVA
• Format: Dissertations
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/29712
• Institution: Institut Teknologi Bandung

The idea of city logistics is to develop urban logistics system that is effective and efficien as well as environmentally friendly. There are four problems related to the development of city logistics. They are economic problem, traffic congestion, environmental problem, and energy consumption. As one of the megacities in the world, DKI Jakarta faces not only inventory problem to meet the demands of its population which is characterized by low availability of fruits and vegetables that is only 76%, but also transportation problem that is traffic congestion. Those problems show that it is needed to develop city logistics in DKI Jakarta to increase availability and to decrease congestion. Development of city logistics related to availability and congestion problems has never been developed before. The importance of considering traffic congestion in developing urban logistics systems is due to traffic conditions that are getting worse lately in many cities in the world. <br /> <br /> There are three entities involved in the supply chain of DKI Jakarta. They are provinces of suppliers, wholesale markets, and traditional markets. City logistics system that will be developed in this research is single-tier city logistics system which also consists of three entities, namely point of supplies, logistics facilities, and point of demands. Point of supplies are provinces of suppliers which will be called as suppliers, logistics facilities are wholesale markets which will be replaced with UCCs (urban consolidation centers), and point of demands are traditional markets which will be called as retail markets. Fundamental concepts of city logistics used are consolidation and coordination. Initiatives of city logistics used are public logistics terminal and cooperative freight transportation system. The products are fruits and vegetables, demands are probabilistic, and following a normal distribution. <br /> <br /> In the real system, the wholesale markets are located in the city, while UCCs in city logistics system are located outside of the city, therefore the optimal locations for UCCs need to be determined. Consolidation concept is used to solve logistics problem which is low availability by increasing service levels through controlling inventory optimally on the three entities involved. Coordination concept is used to solve transportation problem which is traffic congestion by decreasing the number of vehicles through using vehicles together.. Due to the use of vehicles together, then then it is necessary to determine the optimal vehicle route to serve the retail <br /> <br /> there are more than one link, then it is also determined trip assignment in the form of the roads that will be passed. Based on those descriptions, city logistics model that will be developed in this research is related to location decision, inventory control decision, vehicle routing decision, and trip assignment decision. These decisions are solved simultaneously. <br /> <br /> The development of city logistics model in this research is divided into three stage models, namely Model 1 which is integration model of location decision, vehicle routing, and inventory control consisting of one product and one supplier. Model 2 is integration model of location decision, vehicle routing, and inventory control consisting of multi products, multi suppliers, and taking into account traffic congestion. Model 3 is integration model of location decision, vehicle routing, and inventory control consisting multi products, multi suppliers, taking into account traffic congestion, and multi links. <br /> <br /> The problems in the models developed belong to NP-hard problem, so there are two solution methods developed in this research. They are optimal method and heuristic method. Optimal method produces optimal solutions obtained by solver LINGO 12.0 and they are limited to cases for small-scale data. Heuristic method consists of two stages, namely contructive stage and improvement stage. Simulated Annealing algorithm uses at improvement stage to improve the solution. Heuristic method can solve cases for large-scale data so it can be applied to the real system, that is DKI Jakarta. Heuristic method is coded in Matlab R2013a. <br /> <br /> Gap for each heuristic method developed compared to optimal method is 1.13% for Model 1, 5.1% for Model 2, and 3,1% for Model 3. After being applied to the real system, heuristic method for problems in Model 1 can maintain the availability at level of 95%, heuristic method for problems in Model 2 can maintain the availability and reduce the number of vehicles by 73% at the UCCs, and heuristic method for problems in Model 3 can maintain the availability, reduce the number of vehicles, and select less congested link. Besides giving advantages from reducing the number of vehicles and maintain the availability, logistics system with UCC also gives an efficient system cost by 18%.