In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vie...In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vietnam.Vietnam has favorable natural conditions for this energy production.Because it is hot and humid,and it has much rainfall and fertile soil,biomass develops very quickly.Therefore,byproducts from agriculture and forestry are abundant and continuously increasing.However,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta region.Biomass energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable development.Taking advantage of this energy source provides energy for economic development and ensures environmental protection.Due to the abovementioned favorable conditions,many biomass energy plants are being built in Vietnam.Like other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria decisions.In this case,decisionmakers must evaluate many qualitative and quantitative factors.These factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making environment.Therefore,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a Fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative factors.Furthermore,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-makers in other fields can use to find the best supplier.展开更多
This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing...This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing limitations,vehicle destination,etc.Most researchers who previously investigated this problem assumed the vehicle would not return to the depot,but did not consider its final destination.However,by considering 3PL in the B2B e-commerce,the vehicle is required back to the nearest 3PL location with available space.This paper formulates the problem as a mixed integer linear programming(MILP)model with the objective of minimizing the total travel distance.A coordinate representation particle swarm optimization(CRPSO)algorithm is developed to obtain the best delivery sequencing and the capacity of each vehicle.Results of the computational study show that the proposed method provides solution within a reasonable amount of time.Finally,the result compared to PSO also indicates that the CRPSO is effective.展开更多
Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare...Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search processrenders it difficult for agents and consumers to understand the status changes ofobjects. In this study, Python is used to write web crawler and image recognitionprograms to capture object information from the web pages of real estate agents;perform data screening, arranging, and cleaning;compare the text of real estateobject information;as well as integrate and use the convolutional neural networkof a deep learning algorithm to implement image recognition. In this study, dataare acquired from two business-to-consumer real estate agency networks, i.e., theSinyi real estate agent and the Yungching real estate agent, and one consumer-toconsumer real estate agency platform, i.e., the, FiveNineOne real estate agent. Theresults indicate that text mining can reveal the similarities and differences betweenthe objects, list the number of days that the object has been available for sale onthe website, and provide the price fluctuations and fluctuation times during thesales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for realestate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differencesbetween their commodities and other businesses in approximately 2 min, as wellas rapidly determine developable objects via comparison results provided by thesystem. Meanwhile, consumers require less time in searching and comparingprices after they have understood the commodity dynamic information, therebyallowing them to use the most efficient approach to purchase real estate objectsof their interest.展开更多
The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate...The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.展开更多
In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This resear...In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison.The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders.This study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple machines.Based on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big data.Both optimization programs are used in this study and compared to determine which method can better solve the company’s problems.The proposed algorithm is able to improve machine utilization with large-scale problems.展开更多
Since collaborative, planning, forecasting, and replenishment （CPFR） was first proposed in 1998, numerous studies have focused on exploring its implementation in retailing contexts. While a considerable body of rese...Since collaborative, planning, forecasting, and replenishment （CPFR） was first proposed in 1998, numerous studies have focused on exploring its implementation in retailing contexts. While a considerable body of research has emphasized reduced costs, increased sales and improved forecasting ability, there has been a lack of research on the importance of each of the various factors which affect such implementations. In order to find out the critical success factors affecting CPFR implementation, this paper first collected related influence factors regarding adopting CPFR or business to business （B2B） information systems, and further constructed a factor table with a three-layer hierarchical structure. A pair wise analytic hierarchy process （AHP） questionnaire was designed and distributed to experts who were familiar with implementing CPFR in the retailing industry. After questionnaires were returned, we found out the weights of each impact factor by using a fuzzy analytic hierarchy process （fuzzy AHP） approach. The importance of each critical impact factor was investigated, and the paths of the critical success factors were also analyzed. The results of this study can provide more precise information with regard to allocating optimal resources for retailers implementing CPFR.展开更多
This study utilizes fuzzy analytic hierarchy process （FAHP） to analyze decision-making pattems with regard to third-generation wireless communications （3GWC） service adoption, and to provide customized strategic r...This study utilizes fuzzy analytic hierarchy process （FAHP） to analyze decision-making pattems with regard to third-generation wireless communications （3GWC） service adoption, and to provide customized strategic recommendations to suppliers of 3GWC services regarding marketing and resource allocation in the context of the Chinese 3GWC market. First of all, a three-layer hierarchy of 3GWC adoption factors is developed by referring to the relevant literature and industry reports. A questionnaire of pairwise comparisons in the fuzzy AHP format is then designed and distributed to experts familiar with the handset market in Shanghai, China. These surveys are then analyzed using fuzzy AHP to establish an understanding of the weights and impacts of the various factors. The results show that the four most important factors for the adoption of 3GWC systems are： （i） handset price and voice and data-transmission fees; （ii） handset aesthetics; （iii） personalization; and （iv） network coverage. These findings suggest that providers of such services should customize and diversify the content/applications they offer and ensure the speed and reliability of network access. In addition, handset designs should be in accordance with consumer demands. If these steps can be achieved, then consumers will adopt 3GWC services more rapidly.展开更多
文摘In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vietnam.Vietnam has favorable natural conditions for this energy production.Because it is hot and humid,and it has much rainfall and fertile soil,biomass develops very quickly.Therefore,byproducts from agriculture and forestry are abundant and continuously increasing.However,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta region.Biomass energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable development.Taking advantage of this energy source provides energy for economic development and ensures environmental protection.Due to the abovementioned favorable conditions,many biomass energy plants are being built in Vietnam.Like other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria decisions.In this case,decisionmakers must evaluate many qualitative and quantitative factors.These factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making environment.Therefore,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a Fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative factors.Furthermore,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-makers in other fields can use to find the best supplier.
文摘This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing limitations,vehicle destination,etc.Most researchers who previously investigated this problem assumed the vehicle would not return to the depot,but did not consider its final destination.However,by considering 3PL in the B2B e-commerce,the vehicle is required back to the nearest 3PL location with available space.This paper formulates the problem as a mixed integer linear programming(MILP)model with the objective of minimizing the total travel distance.A coordinate representation particle swarm optimization(CRPSO)algorithm is developed to obtain the best delivery sequencing and the capacity of each vehicle.Results of the computational study show that the proposed method provides solution within a reasonable amount of time.Finally,the result compared to PSO also indicates that the CRPSO is effective.
文摘Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search processrenders it difficult for agents and consumers to understand the status changes ofobjects. In this study, Python is used to write web crawler and image recognitionprograms to capture object information from the web pages of real estate agents;perform data screening, arranging, and cleaning;compare the text of real estateobject information;as well as integrate and use the convolutional neural networkof a deep learning algorithm to implement image recognition. In this study, dataare acquired from two business-to-consumer real estate agency networks, i.e., theSinyi real estate agent and the Yungching real estate agent, and one consumer-toconsumer real estate agency platform, i.e., the, FiveNineOne real estate agent. Theresults indicate that text mining can reveal the similarities and differences betweenthe objects, list the number of days that the object has been available for sale onthe website, and provide the price fluctuations and fluctuation times during thesales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for realestate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differencesbetween their commodities and other businesses in approximately 2 min, as wellas rapidly determine developable objects via comparison results provided by thesystem. Meanwhile, consumers require less time in searching and comparingprices after they have understood the commodity dynamic information, therebyallowing them to use the most efficient approach to purchase real estate objectsof their interest.
基金supported by the Ministry of Science and Technology(MOST),Taiwan,R.O.C.(104-2410-H-327-024-).
文摘The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.
文摘In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison.The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders.This study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple machines.Based on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big data.Both optimization programs are used in this study and compared to determine which method can better solve the company’s problems.The proposed algorithm is able to improve machine utilization with large-scale problems.
基金supported by the National Science Council (NSC) of the Executive Yuan, Taiwan. (NSC 97-2221-E-327-022)
文摘Since collaborative, planning, forecasting, and replenishment （CPFR） was first proposed in 1998, numerous studies have focused on exploring its implementation in retailing contexts. While a considerable body of research has emphasized reduced costs, increased sales and improved forecasting ability, there has been a lack of research on the importance of each of the various factors which affect such implementations. In order to find out the critical success factors affecting CPFR implementation, this paper first collected related influence factors regarding adopting CPFR or business to business （B2B） information systems, and further constructed a factor table with a three-layer hierarchical structure. A pair wise analytic hierarchy process （AHP） questionnaire was designed and distributed to experts who were familiar with implementing CPFR in the retailing industry. After questionnaires were returned, we found out the weights of each impact factor by using a fuzzy analytic hierarchy process （fuzzy AHP） approach. The importance of each critical impact factor was investigated, and the paths of the critical success factors were also analyzed. The results of this study can provide more precise information with regard to allocating optimal resources for retailers implementing CPFR.
文摘This study utilizes fuzzy analytic hierarchy process （FAHP） to analyze decision-making pattems with regard to third-generation wireless communications （3GWC） service adoption, and to provide customized strategic recommendations to suppliers of 3GWC services regarding marketing and resource allocation in the context of the Chinese 3GWC market. First of all, a three-layer hierarchy of 3GWC adoption factors is developed by referring to the relevant literature and industry reports. A questionnaire of pairwise comparisons in the fuzzy AHP format is then designed and distributed to experts familiar with the handset market in Shanghai, China. These surveys are then analyzed using fuzzy AHP to establish an understanding of the weights and impacts of the various factors. The results show that the four most important factors for the adoption of 3GWC systems are： （i） handset price and voice and data-transmission fees; （ii） handset aesthetics; （iii） personalization; and （iv） network coverage. These findings suggest that providers of such services should customize and diversify the content/applications they offer and ensure the speed and reliability of network access. In addition, handset designs should be in accordance with consumer demands. If these steps can be achieved, then consumers will adopt 3GWC services more rapidly.
