scholarly journals Implementasi Metode Tabu Search Dalam Penjadwalan Menggunakan Analisa Pieces

2021 ◽  
Vol 6 (2) ◽  
pp. 62
Author(s):  
Made Suci Ariantini ◽  
Ayu Manik Dirgayusari

Nowadays, Scheduling subjects is one of the first steps for starting the teaching and learning process in educational institutions. To do so, The role of teachers and school staff is very important and not easy because it takes a long time to compile it. SMK PGRI 4 Denpasar is one of the schools located in the city of Denpasar which is located on Jalan Kebo Iwa No 8, Padangsambian Kaja, Denpasar, Bali. It is a vocational high school that has a tourism expertise and computer engineering study program. Based on current results of observations and interviews, the process of making the subject schedules that run at SMK PGRI 4 Denpasar is still being done using Microsoft Excel, this has resulted in frequent errors in managing schedules such as conflicting schedule and it takes a long time to correct it. Tabu Search is an optimization method based on local search, where the search process moves from one solution to the next by selecting the best solution which is not classified as a prohibited solution. It is a combinatorial optimization problem-solving method that is incorporated into local search methods. This method aims to streamline the process of finding the best solution of a large-scale (np-hard) combinatorial optimization problem. Tabu search method to optimize the process of making the subject schedule and combined using PIECES analysis (Performance, Information, Economic, Control, Efficiency, Services). From this analysis, several problems will be obtained, which in the end can be identified clearly and more specifically, so that we can conclude some suggestions that will help in designing a new and better system. The Tabu Search method can be used to optimize the process of making the subject schedules at SMK PGRI 4 Denpasar, so that the scheduling process will be more easier than using Microsoft Excel.

Author(s):  
Shaowei Cai ◽  
Chuan Luo ◽  
Haochen Zhang

Maximum Satisfiability (MaxSAT) is an important NP-hard combinatorial optimization problem with many applications and MaxSAT solving has attracted much interest. This work proposes a new incomplete approach to MaxSAT. We propose a novel decimation algorithm for MaxSAT, and then combine it with a local search algorithm. Our approach works by interleaving between the decimation algorithm and the local search algorithm, with useful information passed between them. Experiments show that our solver DeciLS achieves state of the art performance on all unweighted benchmarks from the MaxSAT Evaluation 2016. Moreover, compared to SAT-based MaxSAT solvers which dominate industrial benchmarks for years, it performs better on industrial benchmarks and significantly better on application formulas from SAT Competition. We also extend this approach to (Weighted) Partial MaxSAT, and the resulting solvers significantly improve local search solvers on crafted and industrial benchmarks, and are complementary (better on WPMS crafted benchmarks) to SAT-based solvers.


2018 ◽  
Vol 54(5) ◽  
pp. 72
Author(s):  
Quoc, H.D. ◽  
Kien, N.T. ◽  
Thuy, T.T.C. ◽  
Hai, L.H. ◽  
Thanh, V.N.

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