Journal Articles - Business and Management - 2022

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Browsing Journal Articles - Business and Management - 2022 by Author "Chia-Nan Wang"
  • Publication
    Flow-Shop Scheduling with Transportation Capacity and Time Consideration
    ( 2022)
    Chia-Nan Wang
    ;
    Glen Andrew Porter
    ;
    Ching-Chien Huang
    ;
    Viet Tinh Nguyen
    ;
    Syed Tam Husain
    Planning and scheduling is one of the most important activity in supply chain operation management. Over the years, there have been multiple researches regarding planning and scheduling which are applied to improve a variety of supply chains. This includes two commonly used methods which are mathematical programming models and heuristics algorithms. Flowshop manufacturing systems are seen normally in industrial environments but few have considered certain constraints such as transportation capacity and transportation time within their supply chain. A two-stage flowshop of a single processing machine and a batch processing machine are considered with their capacity and transportation time between twomachines. The objectives of this research are to build a suitable mathematical model capable of minimizing the maximum completion time, to propose a heuristic optimization algorithm to solve the problem, and to develop an applicable program of the heuristics algorithm. AMixed Integer Programming (MIP) model and a heuristics optimization algorithmwas developed and tested using a randomly generated data set for feasibility. The overall results and performance of each approach was compared between the two methods that would assist the decision maker in choosing a suitable solution for their manufacturing line.
  • Publication
    Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain
    ( 2022)
    Le Thi Diem My
    ;
    Chia-Nan Wang
    ;
    Nguyen Van Thanh
    Fertilizer industry in Vietnam and globally have entered the saturation phase. With the growth rate slowing down, this poses challenges for the development impetus of the fertilizer industry in the next period. In fact, over the past few decades, Vietnam’s crop industry has abused excessive investment in chemical fertilizers, with organic fertilizers are rarely used or not at all, limiting crop productivity, increasing pests and diseases. To develop sustainable agriculture, Vietnam’s crop industry must limit the use of chemical fertilizers, increase the use of environmentally friendly organic and naturalmineral fertilizers to produce clean agricultural products which is safe. Therefore, it is necessary to consider and choose the right supplier to ensure the goal of sustainable development. Spherical Fuzzy Analytic Hierarchy Process (SF-AHP), and the combinative distance-based assessment (CODAS) are new Multicriteria Decision Making (MCDM) method which can be used to solve supplier selection problem. This paper uses an effective solution based on a combined the concept of triple bottom line (TBL), SF-AHP and CODAS approach to help agriculture companies that need to select the best fertilizer supplier. This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs, but also develop sustainable agriculture.
  • Publication
    Improving Supply Chain Performance Through Supplier Selection and Order Allocation Problem
    ( 2022)
    Chia-Nan Wang
    ;
    Ming-Cheng Tsou
    ;
    Chih-Hung Wang
    ;
    Viet Tinh Nguyen
    ;
    Pham Ngo Thi Phuong
    Suppliers play the vital role of ensuring the continuous supply of goods to themarket for businesses. If businesses do not maintain a strong bond with their suppliers, they may not be able to secure a steady supply of goods and products for their customers. As a result of failure to deliver products, the production and business activities of the business can be delayed which leads to the loss of customers. Normally, each trading enterprise will have a variety of commodity supply chains withmultiple suppliers. Suppliers play an important role and contribute to the value of the entire supply chain. Should any supplier encounters a problem, the whole supply chain of businesses will be affected and could lead to not guaranteeing the stable supply to the market. Thus, suppliers can be seen as a threat to businesses where they have the ability to increase input prices or decrease the quality of the required products and services they provide. The quantity of the business, and the supply lead time directly affect the operations and reduce the profitability of the business. The paper mainly focuses on the supplier selection problemunder a variety of price level and product families when using a two-phase fuzzy multi-objective linear programming. The objectives of the proposed model are to minimize the total purchasing and ordering cost in order to reduce the quantity of defective materials and the late-delivery components from suppliers. Moreover, the piecewise linear membership function is applied in themodel to determine an optimal solution which is based on the requirement of decision makers under their fuzzy environment. The results of this study can be applied in various business environment and provide a reliable decision tool for choosing potential suppliers relating to these objectives. Based on the results, the company canmake a good decision on supplier selection; therefore, the company can improve the quality and quantity of their final product
  • Publication
    Optimization Model for Selecting Temporary Hospital Locations During COVID-19 Pandemic
    ( 2022)
    Chia-Nan Wang
    ;
    Chien-Chang Chou
    ;
    Hsien-Pin Hsu
    ;
    Van Thanh Nguyen
    ;
    Viet Tinh Nguyen
    The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed, and unnecessary costs may come into play. In this study, a decision support framework using a fuzzy analytic hierarchy process (FAHP) and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital, and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19. A case study is performed for Ho Chi Minh City using the proposed decision-making framework. The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic. The results of the study can be used to assist decisionmakers, such as government authorities and infectious disease experts, in dealing with the current pandemic as well as other diseases in the future.With the entire world facing the global pandemic of COVID-19, many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic. As the number of cases increases exponentially, it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria. As such, the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries
  • Publication
    Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic
    ( 2022)
    Chia-Nan Wang
    ;
    Chao-Fen Pan
    ;
    Viet Tinh Nguyen
    ;
    Syed Tam Husain
    As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in caseswithmultiple potential suppliers.Vietnam’s textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.
  • Publication
    Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing
    ( 2022)
    Chia-Nan Wang
    ;
    Shao-Dong Syu
    ;
    Chien-Chang Chou
    ;
    Viet Tinh Nguyen
    ;
    Dang Van Thuy Cuc
    Agriculture is a key facilitator of economic prosperity and nourishes the huge global population. To achieve sustainable agriculture, several factors should be considered, such as increasing nutrient and water efficiency and/or improving soil health and quality. Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effectiveness of crop yields. Fertilizer supplies most of the necessary nutrients for plants, and it is estimated that at least 30%–50% of crop yields is attributable to commercial fertilizer nutrient inputs. Fertilizer is always a major concern in achieving sustainable and efficient agriculture. Applying reasonable and customized fertilizerswill require a significant increase in the number of formulae, involving increasing costs and the accurate forecasting of the right time to apply the suitable formulae. An alternative solution is given by two-stage production planning under stochastic demand, which divides a planning schedule into two stages. The primary stage has non-existing demand information, the inputs of which are the proportion of raw materials needed for producing fertilizer products, the cost for purchasing materials, and the production cost. The total quantity of purchased material and produced products to be used in the blending process must be defined to meet as small as possible a paid cost. At the second stage, demand appears under multiple scenarios and their respective possibilities. This stage will provide a solution for each occurring scenario to achieve the best profit. The two-stage approach is presented in this paper, the mathematical model of which is based on linear integer programming. Considering the diversity of fertilizer types, themathematicalmodel can advise manufacturers about which products will generate as much as profit as possible. Specifically, two objectives are taken into account. First, the paper’s thesis focuses on minimizing overall system costs, e.g., including inventory cost, purchasing cost, unit cost, and ordering cost at Stage 1.