Pub Date : 2022-03-29DOI: 10.20473/conmatha.v4i1.34549
Laula Ika Setya Rahman, A. B. Pratiwi, H. Suprajitno
This paper aims to solve the problem of Open Vehicle Routing Problem using Seagulls Optimization Algorithm. Open Vehicle Routing Problem (OVRP) is a variation of Vehicle Routing Problem (VRP) which will not return to the depot after visiting the last customer, is different from VRP which requires the vehicle to return to the depot because the company have insufficient number of vehicles for the distribution of products to customers so they must to rent vehicles and this OVRP aims to minimize the total cost of distributing products with the shortest optimal distance to meet the demands of each customer with private vehicles and rental vehicles. Seagulls Optimization Algorithm (SOA) is the algorithm inspired by the behaviour of seagulls in migrating and ways of attacking the pray of seagulls in nature. In general, the process begins with generating the initial position, evaluating the objective function, the migration process, the attacking process to get a new position, compare the objective function for the new position and the old position, update the position and save the best seagulls in each iteration until the maximum iteration is met. The program used to complete OVRP with Seagulls Optimization Algorithm is Borland C++ and implemented using 3 case examples, small data with 18 customers, medium data 50 customers and large data 100 customers. Based on the implementation results, it can be concluded that the higher number of seagulls, iterations and the smaller the control variable value tend to effect minimum cost gained.
{"title":"Penerapan Seagulls Optimization Algorithm untuk Menyelesaikan Open Vehicle Routing Problem","authors":"Laula Ika Setya Rahman, A. B. Pratiwi, H. Suprajitno","doi":"10.20473/conmatha.v4i1.34549","DOIUrl":"https://doi.org/10.20473/conmatha.v4i1.34549","url":null,"abstract":"This paper aims to solve the problem of Open Vehicle Routing Problem using Seagulls Optimization Algorithm. Open Vehicle Routing Problem (OVRP) is a variation of Vehicle Routing Problem (VRP) which will not return to the depot after visiting the last customer, is different from VRP which requires the vehicle to return to the depot because the company have insufficient number of vehicles for the distribution of products to customers so they must to rent vehicles and this OVRP aims to minimize the total cost of distributing products with the shortest optimal distance to meet the demands of each customer with private vehicles and rental vehicles. Seagulls Optimization Algorithm (SOA) is the algorithm inspired by the behaviour of seagulls in migrating and ways of attacking the pray of seagulls in nature. In general, the process begins with generating the initial position, evaluating the objective function, the migration process, the attacking process to get a new position, compare the objective function for the new position and the old position, update the position and save the best seagulls in each iteration until the maximum iteration is met. The program used to complete OVRP with Seagulls Optimization Algorithm is Borland C++ and implemented using 3 case examples, small data with 18 customers, medium data 50 customers and large data 100 customers. Based on the implementation results, it can be concluded that the higher number of seagulls, iterations and the smaller the control variable value tend to effect minimum cost gained.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114991270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Let G(V,E) is a simple graph and connected where V(G) is vertex set and E(G) is edge set. An inclusive local irregularity vertex coloring is defined by a mapping l:V(G) à {1,2,…, k} as vertex labeling and wi : V(G) à N is function of inclusive local irregularity vertex coloring, with wi(v) = l(v) + ∑u∈N(v) l(u). In other words, an inclusive local irregularity vertex coloring is to assign a color to the graph with the resulting weight value by adding up the labels of the vertices that are neighbouring to its own label. The minimum number of colors produced from inclusive local irregularity vertex coloring of graph G is called inclusive chromatic number local irregularity, denoted by Xlisi(G). In this paper, we learn about the inclusive local irregularity vertex coloring and determine the chromatic number of comb product on star graph.
{"title":"Pewarnaan Titik Ketakteraturan Lokal Inklusif pada Hasil Operasi Comb Graf Bintang","authors":"Arika Indah Kristiana, Surya Indriani, E.R Albirri","doi":"10.20473/conmatha.v4i1.33606","DOIUrl":"https://doi.org/10.20473/conmatha.v4i1.33606","url":null,"abstract":"Let G(V,E) is a simple graph and connected where V(G) is vertex set and E(G) is edge set. An inclusive local irregularity vertex coloring is defined by a mapping l:V(G) à {1,2,…, k} as vertex labeling and wi : V(G) à N is function of inclusive local irregularity vertex coloring, with wi(v) = l(v) + ∑u∈N(v) l(u). In other words, an inclusive local irregularity vertex coloring is to assign a color to the graph with the resulting weight value by adding up the labels of the vertices that are neighbouring to its own label. The minimum number of colors produced from inclusive local irregularity vertex coloring of graph G is called inclusive chromatic number local irregularity, denoted by Xlisi(G). In this paper, we learn about the inclusive local irregularity vertex coloring and determine the chromatic number of comb product on star graph.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125958445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-29DOI: 10.20473/conmatha.v4i1.34147
Laurensia Regina Bestari Gepak, Miswanto Miswanto, Cicik Alfiniyah
In social life, difference and diversity is something that cannot be denied by anyone. Starting from differences horizontally concerning ethnicity, language, customs to religion and vertically concerning the political, social, cultural to economic fields. The existence of these many differences can certainly bring positive and negative impacts in social life. With diversity, interaction in society is dynamic, but it results in the emergence of negative attitudes such as egoism and competition between groups. From the occurrence of this can trigger the problem of social inequality in the community. Social inequality can occur because of national development efforts that only focus on economic aspects and forget about social aspects. The purpose of this thesis is to discuss the stability analysis of the predator-prey mathematical model on social dynamics with the Holling type II functional response. From this model analysis, we obtained four equilibrium points, which are the equilibrium point for the extinction of all population (E0) which is unstable, then the equilibrium point for the extinction of the non-poor population and the poor (E1) and the extinction of the non-poor population (E2) which are stable with certain conditions and coexistence (E3) which is to be asymptotically stable. Also in the final section, we perform the numerical simulation to supports the analytical result.
{"title":"Analisis Kestabilan Model Matematika Predator-Prey pada Dinamika Sosial","authors":"Laurensia Regina Bestari Gepak, Miswanto Miswanto, Cicik Alfiniyah","doi":"10.20473/conmatha.v4i1.34147","DOIUrl":"https://doi.org/10.20473/conmatha.v4i1.34147","url":null,"abstract":"In social life, difference and diversity is something that cannot be denied by anyone. Starting from differences horizontally concerning ethnicity, language, customs to religion and vertically concerning the political, social, cultural to economic fields. The existence of these many differences can certainly bring positive and negative impacts in social life. With diversity, interaction in society is dynamic, but it results in the emergence of negative attitudes such as egoism and competition between groups. From the occurrence of this can trigger the problem of social inequality in the community. Social inequality can occur because of national development efforts that only focus on economic aspects and forget about social aspects. The purpose of this thesis is to discuss the stability analysis of the predator-prey mathematical model on social dynamics with the Holling type II functional response. From this model analysis, we obtained four equilibrium points, which are the equilibrium point for the extinction of all population (E0) which is unstable, then the equilibrium point for the extinction of the non-poor population and the poor (E1) and the extinction of the non-poor population (E2) which are stable with certain conditions and coexistence (E3) which is to be asymptotically stable. Also in the final section, we perform the numerical simulation to supports the analytical result.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128882372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-29DOI: 10.20473/conmatha.v4i1.33607
A. I. Kristiana, Muhammad Gufronil Halim, R. Adawiyah
The graph in this paper is a simple and connected graph with V(G) is vertex set and E(G) is edge set. An inklusif local irregularity vertex coloring is defined should be maping l:V(G) à {1,2,…, k} as vertex labeling and wi : V(G) à N is function of inclusive local irregularity vertex coloring, with wi(v) = l(v) + ∑u∈N(v) l(u) in other words, an inclusive local irregularity vertex coloring is to assign a color to the graph with the resulting weight value by adding up the labels of the vertices that are should be neighboring to its own label. The minimum number of colors produced from inclusive local irregularity vertex coloring of graph G is called inclusive chromatic number local irregularity, denoted by Xlisi(G). Should be in this paper, we learn about the inclusive local irregularity vertex coloring and determine the chromatic number on unicyclic graphs.
{"title":"Pewarnaan Titik Ketakteraturan Lokal Inklusif pada Keluarga Graf Unicyclic","authors":"A. I. Kristiana, Muhammad Gufronil Halim, R. Adawiyah","doi":"10.20473/conmatha.v4i1.33607","DOIUrl":"https://doi.org/10.20473/conmatha.v4i1.33607","url":null,"abstract":"The graph in this paper is a simple and connected graph with V(G) is vertex set and E(G) is edge set. An inklusif local irregularity vertex coloring is defined should be maping l:V(G) à {1,2,…, k} as vertex labeling and wi : V(G) à N is function of inclusive local irregularity vertex coloring, with wi(v) = l(v) + ∑u∈N(v) l(u) in other words, an inclusive local irregularity vertex coloring is to assign a color to the graph with the resulting weight value by adding up the labels of the vertices that are should be neighboring to its own label. The minimum number of colors produced from inclusive local irregularity vertex coloring of graph G is called inclusive chromatic number local irregularity, denoted by Xlisi(G). Should be in this paper, we learn about the inclusive local irregularity vertex coloring and determine the chromatic number on unicyclic graphs.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121583582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-29DOI: 10.20473/conmatha.v4i1.34393
Retno Maharesi
The study discusses problems related to the formation of a decision tree based on a collection of evaluation data records obtained from a number of car buyers. This secondary data was obtained from the UCL machine learning website. The purpose of this research is to produce a prototype algorithm for obtaining an inductive decision tree based on Chi-square statistics. An inductive decision tree formation method based on the Chi-square contingency test was compared with a decision tree obtained using a machine learning algorithm which was done using RapidMiner5 software. The work to produce an inductive decision tree was carried out by first processing data using Microsoft excel and next processed using SPSS software, on the crosstabs descriptive menu. The results of the two methods provide some kind of similar rules, in terms of the order of priority of the variables that most influencing people's decision to accept an automotive product. The formation of the decision tree uses a random sampling of size 300 data records among 1729 respondent data records in the car evaluation database. The resulting decision tree should have a minimal structure like a binary tree. This is possible because its formation is based on the statistical inferential method, so it does not require a separate pruning process as an addition step in the C4.5 algorithm, which actually this algorithm also considers aspects of the statistical significance.
{"title":"Pembentukan Model Pohon Keputusan pada Database Car Evaluation Menggunakan Statistik Chi-Square","authors":"Retno Maharesi","doi":"10.20473/conmatha.v4i1.34393","DOIUrl":"https://doi.org/10.20473/conmatha.v4i1.34393","url":null,"abstract":"The study discusses problems related to the formation of a decision tree based on a collection of evaluation data records obtained from a number of car buyers. This secondary data was obtained from the UCL machine learning website. The purpose of this research is to produce a prototype algorithm for obtaining an inductive decision tree based on Chi-square statistics. An inductive decision tree formation method based on the Chi-square contingency test was compared with a decision tree obtained using a machine learning algorithm which was done using RapidMiner5 software. The work to produce an inductive decision tree was carried out by first processing data using Microsoft excel and next processed using SPSS software, on the crosstabs descriptive menu. The results of the two methods provide some kind of similar rules, in terms of the order of priority of the variables that most influencing people's decision to accept an automotive product. The formation of the decision tree uses a random sampling of size 300 data records among 1729 respondent data records in the car evaluation database. The resulting decision tree should have a minimal structure like a binary tree. This is possible because its formation is based on the statistical inferential method, so it does not require a separate pruning process as an addition step in the C4.5 algorithm, which actually this algorithm also considers aspects of the statistical significance.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124051723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.20473/conmatha.v3i2.30493
Riris Nur Patria Putri
Predation is interaction between predator and prey, where predator preys prey. So predators can grow, develop, and reproduce. In order for prey to avoid predators, then prey needs a refuge. In this thesis, a predator-prey model with refuge factor using Holling type III response function which has three populations, i.e. prey population in the refuge, prey population outside the refuge, and predator population. From the model, three equilibrium points were obtained, those are extinction of the three populations which is unstable, while extinction of predator population and coexistence are asymptotic stable under certain conditions. The numerical simulation results show that refuge have an impact the survival of the prey.
{"title":"Analisis Kestabilan Model Predator-Prey dengan Adanya Faktor Tempat Persembunyian Menggunakan Fungsi Respon Holling Tipe III","authors":"Riris Nur Patria Putri","doi":"10.20473/conmatha.v3i2.30493","DOIUrl":"https://doi.org/10.20473/conmatha.v3i2.30493","url":null,"abstract":"Predation is interaction between predator and prey, where predator preys prey. So predators can grow, develop, and reproduce. In order for prey to avoid predators, then prey needs a refuge. In this thesis, a predator-prey model with refuge factor using Holling type III response function which has three populations, i.e. prey population in the refuge, prey population outside the refuge, and predator population. From the model, three equilibrium points were obtained, those are extinction of the three populations which is unstable, while extinction of predator population and coexistence are asymptotic stable under certain conditions. The numerical simulation results show that refuge have an impact the survival of the prey.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121269800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.20473/conmatha.v3i2.29887
Tuhfatul Janan, Moh. Imam Utoyo, F. Fatmawati
Dalam penelitian ini, diberikan hubungan antara ideal dan kode siklik serta sifat-sifat polinomial pembangun dari ideal dan dimensi dari kode siklik. Sifat-sifat tersebut antara lain hubungan antara polinomial pembangun dari ideal dengan polinomial monik dengan derajat terkecil di ideal, eksistensi dan ketunggalan dari polinomial pembangun dari ideal, hubungan antara polinomial pembangun dari ideal dengan pembagi monik dari , dan hubungan antara derajat dari polinomial pembangun dari ideal dan dimensi dari kode siklik.
{"title":"Polinomial Pembangun dari Ideal dan Dimensi dari Kode Siklik","authors":"Tuhfatul Janan, Moh. Imam Utoyo, F. Fatmawati","doi":"10.20473/conmatha.v3i2.29887","DOIUrl":"https://doi.org/10.20473/conmatha.v3i2.29887","url":null,"abstract":"Dalam penelitian ini, diberikan hubungan antara ideal dan kode siklik serta sifat-sifat polinomial pembangun dari ideal dan dimensi dari kode siklik. Sifat-sifat tersebut antara lain hubungan antara polinomial pembangun dari ideal dengan polinomial monik dengan derajat terkecil di ideal, eksistensi dan ketunggalan dari polinomial pembangun dari ideal, hubungan antara polinomial pembangun dari ideal dengan pembagi monik dari , dan hubungan antara derajat dari polinomial pembangun dari ideal dan dimensi dari kode siklik.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122645032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.20473/conmatha.v3i2.29802
Ilham Ramadhani, Aulia Damayanti, Edi Winarko
Every country has a currency as a medium of exchange and the movement of its exchange rate can affect the economy of the country. In Indonesia, since the freely floating exchange rates system has been applied in August 1997, the value of rupiah currency in the foreign exchange market can change at any time. Considering the massive impacts of exchange rate fluctuation on the economy, then forecasting the exchange rate of rupiah against the US dollar is important to help Indonesia’s economic growth. The aims of this thesis is to predict the estimated exchange rate of rupiah against the US dollar in the future by using hybrid artificial neural network extreme learning machine (ELM) method and firefly algorithm (FA). In the training process, ELM-FA hybrid has a role to obtain the best weight and bias. The weight and bias that obtained will be used for forecasting and to know the success rate of the training process, the validation test process is required. Based on the implementation of program and simulation for some parameter values on the exchange rate data from Jan 2015 until Jan 2018, with four input and hidden nodes, and one output node, obtained the smallest MSE of the training is 0.000480513 with MSE of the testing is 0.0000854107. The relatively small MSE value indicates that ELM-FA network is able to recognize the data pattern well and able to predict the test data well.
{"title":"Hybrid Extreme Learning Machine dan Firefly Algorithm untuk Meramalkan Nilai Tukar Rupiah terhadap Dolar","authors":"Ilham Ramadhani, Aulia Damayanti, Edi Winarko","doi":"10.20473/conmatha.v3i2.29802","DOIUrl":"https://doi.org/10.20473/conmatha.v3i2.29802","url":null,"abstract":"Every country has a currency as a medium of exchange and the movement of its exchange rate can affect the economy of the country. In Indonesia, since the freely floating exchange rates system has been applied in August 1997, the value of rupiah currency in the foreign exchange market can change at any time. Considering the massive impacts of exchange rate fluctuation on the economy, then forecasting the exchange rate of rupiah against the US dollar is important to help Indonesia’s economic growth. The aims of this thesis is to predict the estimated exchange rate of rupiah against the US dollar in the future by using hybrid artificial neural network extreme learning machine (ELM) method and firefly algorithm (FA). In the training process, ELM-FA hybrid has a role to obtain the best weight and bias. The weight and bias that obtained will be used for forecasting and to know the success rate of the training process, the validation test process is required. Based on the implementation of program and simulation for some parameter values on the exchange rate data from Jan 2015 until Jan 2018, with four input and hidden nodes, and one output node, obtained the smallest MSE of the training is 0.000480513 with MSE of the testing is 0.0000854107. The relatively small MSE value indicates that ELM-FA network is able to recognize the data pattern well and able to predict the test data well.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129173104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.20473/conmatha.v3i2.29853
Harmanus Batkunde
This paper discussed about construction of some quotients spaces of the 2-inner product spaces. On those quotient spaces, we defined an inner product with respect to a linear independent set. These inner products was derived from the -inner product. We then defined a norm which induced by the inner product in these quotient spaces.
{"title":"Norms on Quotient Spaces of The 2-Inner Product Space","authors":"Harmanus Batkunde","doi":"10.20473/conmatha.v3i2.29853","DOIUrl":"https://doi.org/10.20473/conmatha.v3i2.29853","url":null,"abstract":"This paper discussed about construction of some quotients spaces of the 2-inner product spaces. On those quotient spaces, we defined an inner product with respect to a linear independent set. These inner products was derived from the -inner product. We then defined a norm which induced by the inner product in these quotient spaces.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134131687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.20473/conmatha.v3i2.29670
Quinn Nathania P.J.Y, A. B. Pratiwi, H. Suprajitno
This paper has purpose to solve Container Stowage Problem (CSP) for 20 feet container using Whale Optimization Algorithm (WOA). CSP is a problem discussing about how to stowage a container on the ship where the purpose to minimize the unloading time. Moreover, 20 feet container is one of container types. WOA is a recently developed swarm-based metaheuristic algorithm that is based on the bubble net hunting maneuver technique of humpback whales for solving complex optimization problems. WOA had three procedures, first encircling prey, second bubble-net attacking method or exploitation phase, and third search for prey or exploration phase. WOA application program or resolving solve CSP for 20 feet container was made by using Borland C++ programming language which was implemented in three cases types of CSP data, first, the small data taking about nine containers with the number of bays, rows and tiers, respectively, are 4, 4, 4. The second and third data was medium data and big data with 62 containers and 95 containers each data, and had the number of bays, rows and tiers, respectively, are 14, 4, 5. After executing the program can be concluded the unloading time will be better if the number of whales is larger, while the number of iterations and the number of parameter control for shape of a logaritma spiral don’t affect the solution.
{"title":"Penyelesaian Container Stowage Problem untuk Kontainer Ukuran 20 Feet menggunakan Whale Optimization Algorithm","authors":"Quinn Nathania P.J.Y, A. B. Pratiwi, H. Suprajitno","doi":"10.20473/conmatha.v3i2.29670","DOIUrl":"https://doi.org/10.20473/conmatha.v3i2.29670","url":null,"abstract":"This paper has purpose to solve Container Stowage Problem (CSP) for 20 feet container using Whale Optimization Algorithm (WOA). CSP is a problem discussing about how to stowage a container on the ship where the purpose to minimize the unloading time. Moreover, 20 feet container is one of container types. WOA is a recently developed swarm-based metaheuristic algorithm that is based on the bubble net hunting maneuver technique of humpback whales for solving complex optimization problems. WOA had three procedures, first encircling prey, second bubble-net attacking method or exploitation phase, and third search for prey or exploration phase. WOA application program or resolving solve CSP for 20 feet container was made by using Borland C++ programming language which was implemented in three cases types of CSP data, first, the small data taking about nine containers with the number of bays, rows and tiers, respectively, are 4, 4, 4. The second and third data was medium data and big data with 62 containers and 95 containers each data, and had the number of bays, rows and tiers, respectively, are 14, 4, 5. After executing the program can be concluded the unloading time will be better if the number of whales is larger, while the number of iterations and the number of parameter control for shape of a logaritma spiral don’t affect the solution.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124930045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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