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Daniel Mulyono Kresnadi
Mahasiswa Program Studi Magister Teknik Sipil, Universitas Kristen Petra, Surabaya
Civil Engineering, Building, Construction & Architecture

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The OPTIMASI SUPPLY CHAIN READY MIX CONCRETE PADA PERUSAHAAN PT X DI SURABAYA MENGGUNAKAN METODE METAHEURISTIK Daniel Mulyono Kresnadi; Doddy Prayogo
Dimensi Utama Teknik Sipil Vol 8 No 1 (2021): April 2021
Publisher : Program Studi Magister Teknik Sipil - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (941.623 KB) | DOI: 10.9744/duts.8.1.35-48

Abstract

Infrastructure development is followed by an increase in demand for ready-mix concrete (RMC). Some failures in delivering RMC on time would delay construction performance or the truck would need to wait at the construction site, so the delivered concrete became useless if it exceeded the concrete setting time limit. This research optimizes the supply chain of ready mix concrete based on real-time data from a batching plant in Surabaya by using the metaheuristic method. The metaheuristic method used in this research are Particle Swarm Optimization (PSO) and Symbiotic Organisms Search (SOS), and also compares the performance of both metaheuristic algorithms, because both algorithms have proven effective in solving various optimization problems. The objective function of this research is to minimize the total waiting times of mixer trucks. The results showed that the SOS algorithm has better performance than the PSO algorithm, which gets lower total waiting times of 100,863 hours.
The OPTIMASI SUPPLY CHAIN READY MIX CONCRETE PADA PERUSAHAAN PT X DI SURABAYA MENGGUNAKAN METODE METAHEURISTIK Daniel Mulyono Kresnadi; Doddy Prayogo
Dimensi Utama Teknik Sipil Vol. 8 No. 1 (2021): April 2021
Publisher : Program Studi Magister Teknik Sipil - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/duts.8.1.35-48

Abstract

Infrastructure development is followed by an increase in demand for ready-mix concrete (RMC). Some failures in delivering RMC on time would delay construction performance or the truck would need to wait at the construction site, so the delivered concrete became useless if it exceeded the concrete setting time limit. This research optimizes the supply chain of ready mix concrete based on real-time data from a batching plant in Surabaya by using the metaheuristic method. The metaheuristic method used in this research are Particle Swarm Optimization (PSO) and Symbiotic Organisms Search (SOS), and also compares the performance of both metaheuristic algorithms, because both algorithms have proven effective in solving various optimization problems. The objective function of this research is to minimize the total waiting times of mixer trucks. The results showed that the SOS algorithm has better performance than the PSO algorithm, which gets lower total waiting times of 100,863 hours.
Co-Authors Doddy Prayogo