Article thumbnail

Penerapan Algoritma Consultant-Guided Search dalam Masalah Penjadwalan Job Shop untuk Meminimasi Makespan

By Hotna Marina Sitorus, Cynthia P. Juwono and Yogi Purnawan

Abstract

This research uses the Consultant-Guided Search (CGS) algorithm to solve job shop scheduling problems minimizing makespan. CGS is a metaheuristics inspired by people making decisions based on consultant’s recommendations. A number of cases from literatures is developed to evaluate the optimality of this algorithm. CGS is also tested against other metaheuristics, namely Genetic Algorithms (GA) and Artificial Immune Systems (AIS) for the same cases. Performance evaluations are conducted using the best makespan obtained by these algorithms. From computational results, it is shown that CGS is able to find 3 optimal solutions out of 10 cases. Overall, CGS performs better compared to the other algorithms where its solution lies within 0 - 6,77% from the optimal solution, averaging only 2,15%. Futhermore, CGS outperforms GA in 7 cases and performs equally well in the other 3 cases. CGS is also better than AIS in 8 cases and is equally well in only 2 cases

Topics: Industrial engineering. Management engineering, T55.4-60.8
Publisher: LPPM Universitas Katolik Parahyangan
Year: 2017
OAI identifier: oai:doaj.org/article:54ee8d9f716243b78222573859b0cc92
Journal:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://doaj.org/toc/2339-1499 (external link)
  • https://doaj.org/toc/0216-1036 (external link)
  • https://doaj.org/article/54ee8... (external link)
  • http://journal.unpar.ac.id/ind... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.