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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Siti Suzlin Supadi
University of Malaya
Computer Science & IT Electrical & Electronics Engineering

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The robust counterpart open capacitated vehicle routing problem with time windows on waste transport problems Evi Yuliza; Fitri Maya Puspita; Siti Suzlin Supadi
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.491 KB) | DOI: 10.11591/eei.v9i5.2439

Abstract

The optimum route for garbage transport vehicles is restricted by vehicle capacity and time windows that the garbage transport vehicle starts at the origin and does not return to the origin. The problem of transporting waste routes is a robust optimization problem where the amount of waste in an area and travel time is uncertain. In the real world, traffic jams and vehicle engine damage can cause delays. This paper proposes the robust counterpart open capacitated vehicle routing problem (denoted by RCOCVRP) with soft time windows model. The aim of RCOCVRP with soft time windows model is to find schedule and optimum route of transporting waste. This model calculation uses LINGO software and GAMS software. Finally for the evaluation of the RCOCVRP model with soft time windows on the proposed waste transportation problem is conducted so that it hasa feasible solution.
The Bender’s decomposition model to optimize temporary waste disposal sites based on general algebraic modeling system Sisca Octarina; Fitri Maya Puspita; Endro Setyo Cahyono; Evi Yuliza; Pebriyanti Simanjuntak; Siti Suzlin Supadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 2: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i2.pp666-679

Abstract

Waste constitutes a substantial problem in urban and residential locales, as the volume of refuse escalates in tandem with population increase, deteriorating community quality of life. One solution to this problem is to provide temporary waste disposal sites (TWDS). This research discussed optimizing TWDS in the Sukarami Subdistrict, Palembang City, which consists of seven villages. The current TWDS in the Sukarami Subdistrict is irregular, with some sites located close together and others far apart. The optimization problem is solved by formulating the set covering problem (SCP) model, namely the set covering location problem (SCLP), the p-Median problem, and the Bender’s decomposition model. All models were solved using the general algebraic modeling system (GAMS) software. The research introduces a Bender’s decomposition model based on the SCLP model. The Sukarami Subdistrict has 29 TWDS located in only five villages. Using the SCLP and Bender’s decomposition models, the study identified 19 optimal TWDS in the Sukarami Subdistrict. Based on the solution of the p-Median problem, there are seven TWDS that can meet each village’s demand. This study recommends the optimal TWDS obtained from the Bender’s decomposition model. Additionally, two TWDS are recommended to be added, each in Sukodadi and Talang Betutu villages.
Probabilistic inventory modeling for chlorine gas using minitab and python: a comparative study of demand distributions Oki Dwipurwani; Fitri Maya Puspita; Siti Suzlin Supadi; Evi Yuliza
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i3.pp1026-1037

Abstract

The availability of chlorine gas (Cl2) is a critical component in the drinking water disinfection process at the regional drinking water company (PDAM), as it plays a vital role in ensuring microbiological safety. Disruptions in the chlorine gas supply may lead to interruptions in water distribution and pose significant public health risks. This study investigates the application of a probabilistic (Q, r) inventory model for managing chlorine gas stock, incorporating several probability distributions that satisfy the underlying model assumptions. The resulting optimal inventory policies derived from each distribution are then compared. Chlorine gas demand forecasting is also performed using the seasonal autoregressive integrated moving average (SARIMA) model. The objective of this research is to generate an optimal inventory policy and accurate demand forecasts, with the entire implementation carried out in Python software. The results show that the best model obtainis the SARIMA (0,1,0)(0,1,1)12 model, with a MAPE value of 5.48%, and that the chlorine gas demand data follow normal, gamma, exponential, and erlang probability distributions. The comparison results show that the optimal policy of the gamma probabilistic model provides the best results, as well as being better than Normal and exponential policies in previous studies.
Co-Authors Endro Setyo Cahyono, Endro Setyo Evi Yuliza, Evi Fitri Maya Puspita Oki Dwipurwani Pebriyanti Simanjuntak Sisca Octarina