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Dana Marsetiya Utama

Bio: Dana Marsetiya Utama is an academic researcher from Dana Corporation. The author has contributed to research in topics: Flow shop scheduling & Computer science. The author has an hindex of 8, co-authored 54 publications receiving 247 citations.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: The findings showed that HWOA is more competitive in minimizing the total distribution cost of GVRP as compared to other algorithms.
Abstract: In recent years, issues on global warming and climate change have received public attention. One of the causes of this problem is carbon emissions in the transportation sector. Therefore, a proper ...

33 citations

Journal ArticleDOI
TL;DR: This paper attempts to review the Vehicle Routing Problem for Perishable Goods and shows the metaheuristic algorithm to be a popular optimization method for solving single and multi-objective problems.
Abstract: Vehicle Routing Problem (VRP) is the problem for finding optimal routes in the distribution system, and this problem needs attention because it can improve distribution performance. One of the prob...

28 citations

Journal ArticleDOI
TL;DR: The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms and the computation time is also included in the analysis.
Abstract: In the industrial sector, transportation plays an essential role in distribution. This activity impacts climate change and global warming. One of the critical problems in distribution is the green vehicle routing problem (G-VRP). This study focuses on G-VRP for a single distribution center. The objective function is to minimize the distribution costs by considering fuel costs, carbon costs, and vehicle use costs. This research aims to develop the hybrid butterfly optimization algorithm (HBOA) to minimize the distribution costs on G-VRP. It was inspired by the butterfly optimization algorithm (BOA), which was by combining the tabu search (TS) algorithm and local search swap and flip strategies. BOA is a new metaheuristic algorithm that has been successfully applied in various engineering fields. Experiments were carried out to test the parameters of the proposed algorithm and vary the speed of vehicles. The proposed algorithm was also compared with several procedures of prior study. The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms. Moreover, the computation time is also included in the analysis.

26 citations

Journal ArticleDOI
26 Feb 2019
TL;DR: The algorithm proposed is the Hybrid Sine Cosine Algorithm (HSCA) to solve FSSDS problems to reduce carbon emissions and showed better performance compared to the simulated annealing and cross-entropy algorithm.
Abstract: Recently, carbon emissions have become a major environmental problem. In the industrial sector, carbon emissions account for half of the world's total carbon emissions. This article discusses the issue of scheduling Flow Shop Sequence Dependent Setup (FSSDS). It aims to minimize carbon emissions. The algorithm proposed is the Hybrid Sine Cosine Algorithm (HSCA) to solve FSSDS problems to reduce carbon emissions. We offered one of some search agents in the SCA use NEH. The algorithm is used for some test different jobs and machines. Several experiments were carried out to test the parameters and effectiveness of the algorithm. The parameters used in the trial are population and iteration. As a result, several parameters were proposed to HSCA to minimize carbon emissions. In the effectiveness test, the HSCA showed better performance compared to the simulated annealing and cross-entropy algorithm.

25 citations


Cited by
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01 Jan 2012

1,072 citations

Journal ArticleDOI
TL;DR: The Sine Cosine Algorithm (SCA) as mentioned in this paper is a population-based optimization algorithm introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions.
Abstract: The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions. After providing an overview of the SCA algorithm, we survey a number of SCA variants and applications that have appeared in the literature. We then present the results of a series of computational experiments to validate the performance of the SCA against similar algorithms.

179 citations

Journal Article
TL;DR: A Hybrid Genetic Algorithm, combining genetic algorithm with neural network, for Job shop scheduling problem is described and it is shown that this method is good for complex production scheduling, at calculation time and goodness.
Abstract: The neural network model of Job shop scheduling problem is built. The characteristics and properties of its solutions are studied. A Hybrid Genetic Algorithm, combining genetic algorithm with neural network, for Job shop scheduling problem is described. The corresponding simulation shows that our method is good for complex production scheduling, at calculation time and goodness.

149 citations

Journal ArticleDOI
TL;DR: An overview of the Ant Lion Optimizer (ALO) applications and a review of ALO variants is presented, which include binary, modification, hybridization, enhanced, and others.
Abstract: This paper introduces a comprehensive overview of the Ant Lion Optimizer (ALO). ALO is a novel metaheuristic swarm-based approach introduced by Mirjalili in 2015 to emulate the hunting behavior of ant lions in nature life. The review is highlighted the applications that are utilized ALO algorithm to solve various optimization problems. In ALO, the best solution is determined to enhance the performance of the functional and efficient during the optimization process by finding the minimum or maximum values to solve a certain problem. Metaheuristic algorithms have become the focus of research due to introduce of decision-making and asses the benefits in solving various optimization problems. Also, a review of ALO variants is presented in this paper such as binary, modification, hybridization, enhanced, and others. The classifications of the ALO’s applications include the benchmark functions, machine learning applications, networks applications, engineering applications, software engineering, and Image processing. Finally, According to the reviewed papers published in the literature, the ALO algorithm is mostly utilized in solving various optimization problems. Presenting an overview and reviewing the ALO applications are the main aims of this review paper.

110 citations

Journal ArticleDOI
TL;DR: The findings showed that HWOA is more competitive in minimizing the total distribution cost of GVRP as compared to other algorithms.
Abstract: In recent years, issues on global warming and climate change have received public attention. One of the causes of this problem is carbon emissions in the transportation sector. Therefore, a proper ...

33 citations