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Design of Vehicle Routes for Rice Distribution System in Bandung Using Simulated Annealing Algorithm Nova Indah Saragih; Peri Turnip
Jurnal Rekayasa Sistem Industri Vol. 11 No. 2 (2022): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.683 KB) | DOI: 10.26593/jrsi.v11i2.5842.211-220

Abstract

VRP (vehicle routing problem) belongs to the problem of NP-hard. It makes the computation time becoming longer as the number of data increases. This statement is in accordance with previous research which solved the VRP for the rice distribution system in Bandung which consisted of 40 demand points in the form of traditional markets using the optimal method. The computational time required is 167 hours 52 minutes 38 seconds. Therefore, a heuristic method is needed to solve VRP with a more efficient computation time and an acceptable solution. The purpose of this paper is to complete the VRP by using an annealing simulation to design a rice distribution system in Bandung. Simulated annealing (SA) is a local search algorithm (meta-heuristic) that is able to get out of the local optimum. Its ease of implementation, the use of hill-climbing motions to avoid local optimal, and the convergent nature, have made SA a popular technique over the past two decades. After comparing the results to the ILP model, the computational experiments show what the SA algorithm developed in this paper is able to produce a relatively small gap in terms of total transportation cost, which is 1.26%. This paper has also succeeded in improving the previous paper by reducing the computation time to 19 seconds using the developed SA algorithm.  
Measurement model for national logistics cost of Indonesia Saragih, Nova Indah; Turnip, Peri
Journal Industrial Servicess Vol 10, No 2 (2024): October 2024
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jiss.v10i2.27313

Abstract

National logistics costs are a crucial indicator for nations to monitor and evaluate the efficiency of their logistics activities. They also serve as an essential foundation for economic growth. A lack of data is the primary challenge in measuring national logistics costs. To accurately assess these costs, countries must have reliable statistics on transportation and inventory. Without such data, estimating logistics costs becomes highly challenging, and the results are often unreliable. This research aims to develop a national logistics cost model for Indonesia. The key contribution of this study is that it represents the first effort to create a logistics cost model specifically for Indonesia. The model is developed based on the frameworks used in the United States of America, the Republic of Korea, and South Africa, adjusted to fit the data available in Indonesia. It comprises three main components: transportation costs, inventory handling costs, and administrative costs. Transportation and inventory handling costs are modeled based on the approach used in the Republic of Korea, while administrative costs are based on the model from the United States of America. This study introduces 25 calculation scenarios, and based on the selected scenario, the average national logistics cost of Indonesia from 2004 to 2010 is found to be 27.94% of GDP.
Tabu Search Algorithm for Solving a Location-Routing-Inventory Problem Saragih, Nova Indah; Turnip, Peri
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.234

Abstract

Location decisions, inventory control, and vehicle routing are interrelated decisions. Inventory control decisions, such as order lot size and order frequency, affect both inventory and transportation costs. Failure to take inventory and transportation costs into consideration when determining location decisions can lead to suboptimality since they have a large impact on inventory and transportation costs. Therefore, how to decide locations, determine vehicle routing, and control inventory optimally, or location-routing-inventory problem (LRIP), becomes an important issue to design logistics systems. The objective of this paper is to develop a heuristic method base on Tabu Search (TS) to solve a LRIP. The contribution of this paper which is the heuristic method based on TS to solve a LRIP has never been developed before. TS is a type of metaheuristic. The success of TS is due to its ability to direct the search process so as not to get trapped in the local optimum, in large part, like many other metaheuristics. TS has been widely used to solve complex combinatorial optimization problems. The result of the computational comparison show that the heuristic method can provide a relatively small average gap of 3.20% compared to the optimal method. Application of the proposed heuristic is done in DKI Jakarta.
Location Selection of Surabaya Landfill using Integration of the PROMETHEE and the AHP Methods Nova Indah Saragih; Peri Turnip
Jurnal INTECH Teknik Industri Universitas Serang Raya Vol. 12 No. 1 (2026): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/intech.v12i1.11961

Abstract

Surabaya is the second-largest city in Indonesia. Like other major cities, Surabaya faces waste problems. The amount of waste produced by Surabaya residents has increased annually. This is partly due to the growing population. Currently, municipal waste management is still centralized in the Benowo Landfill. Owing to the increasing amount of waste and limited land available at the Benowo Landfill, a new landfill is needed. The selection of a landfill site is a complex problem because the selection criteria are multiple and conflicting with one another. The method used in this study is an integration of the PROMETHEE and AHP methods. The two MCDM methods were used to complement each other, and the weaknesses of one method were corrected by utilizing the strengths of the other, resulting in a better solution. This study aims to determine the location of a new landfill in Surabaya using the integration of the PROMETHEE and AHP methods. Based on the data processing that has been done, it is known that the new landfill location is in the Rungkut District.