LOCATION ALLOCATION PROBLEM, TABU SEARCH, MIXED INTEGER LINEAR PROGRAMMING

• Main Author: AFIFI HUSNA NIM 23416046, NABILA
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/29440
• Institution: Institut Teknologi Bandung

Along with the increasing energy consumption in Indonesia, the Directorate General of Oil and Gas as the government must be able to respond to the needs of oil and gas consumption with a quick and effective response. One of the challenges being faced by the Directorate General of Oil and Gas is the inequality of the distribution of Fuel Filling Station General (gas stations) in Indonesia and the optimal number of gas stations, especially in growing areas. One such area is the Bandung District that located in the major metropolitan areas in West Java called Bandung Raya Region. <br /> <br /> <br /> <br /> <br /> <br /> The number and location of gas stations in Bandung District is still considered not evenly distributed, where there are many stations that are still centralized at a point of the area and many of areas do not have gas station. Other than that,from 31 district of Bandung Raya Region, there aren’t a single gas stations on the eleven district. Even though the point of the regulation of gas station from Directorate General of Oil and gas is to respond and facilitate the customer.PT Pertamina also has to fulfill this challenge, in addition to precisely but also efficiently which can minimize the cost that is involved. <br /> <br /> <br /> <br /> <br /> <br /> Therefore, through this research will be developed a model of planning the amount and distribution of gas stations through multi-product location and allocation model, multi-period, 2 echelon (MCMP2S) that can meet the needs of consumers with minimal cost. In the model built, there are some considerations of heterogeneous tanker truck vehicles used for delivery from Depo to gas stations. The problems studied are large-scale and difficult to solve with LINGO due to large computing time. Therefore, the meta-heuristic taboo search algorithm was developed to solve it. <br /> <br /> <br /> <br /> <br /> <br /> The 2 phase taboo search algorithm built algorithm is able to reach the near optimal solution, where the quality of the solution averages 99.7% of the solution quality from LINGO. In addition, with taboo search algorithm the time of computing can be saved on average by 50%. The built algorithm has been verified and validated to solve the problems studied