Tran Quynh Le
Bio: Tran Quynh Le is an academic researcher from Sirindhorn International Institute of Technology. The author has contributed to research in topics: Total cost & Sustainability. The author has an hindex of 1, co-authored 2 publications receiving 6 citations.
26 Nov 2020
TL;DR: The results indicate that, although the objective function (total cost) increased by 20%, the problem became more realistic to address when the model was utilized to solve the constraints of node capacity, detour, and vehicle utilization.
Abstract: This paper develops a mathematical model for intermodal freight transportation. It focuses on determining the flow of goods, the number of vehicles, and the transferred volume of goods transported from origin points to destination points. The model of this article is to minimize the total cost, which consists of fixed costs, transportation costs, intermodal transfer costs, and CO2 emission costs. It presents a mixed integer linear programming (MILP) model that minimizes total costs, and a fuzzy mixed integer linear programming (FMILP) model that minimizes imprecise total costs under conditions of uncertain data. In the models, node capacity, detour, and vehicle utilization are incorporated to estimate the performance impact. Additionally, a computational experiment is carried out to evaluate the impact of each constraint and to analyze the characteristics of the models under different scenarios. Developed models are tested using real data from a case study in Southern Vietnam in order to demonstrate their effectiveness. The results indicate that, although the objective function (total cost) increased by 20%, the problem became more realistic to address when the model was utilized to solve the constraints of node capacity, detour, and vehicle utilization. In addition, on the basis of the FMILP model, fuzziness is considered in order to investigate the impact of uncertainty in important model parameters. The optimal robust solution shows that the total cost of the FMILP model is enhanced by 4% compared with the total cost of the deterministic model. Another key measurement related to the achievement of global sustainable development goals is considered, reducing the additional intermodal transfer cost and the cost of CO2 emissions in the objective function.
TL;DR: In this paper , the integrated entropy-CoCoSo approach for evaluating the sustainability of road transportation systems is introduced, and the framework process is proposed to define the weight of the decision criteria based on the real data.
Abstract: Road haulage solutions are incredibly adaptable, having the capacity to link domestically and internationally. Road transportation offers a greener, more efficient, and safer future through sophisticated technology. Symmetry and asymmetry exist widely in industrial applications, and logistics and supply chains are no exception. The multi-criteria decision-making (MCDM) model is considered as a complexity tool to balance the symmetry between goals and conflicting criteria. This study can assist stakeholders in understanding the current state of transportation networks and planning future sustainability measures through the MCDM approach. The main purpose of this paper is to evaluate and compare the sustainable development of existing road transportation systems to determine whether any of them can be effectively developed in the Organization for Economic Cooperation and Development (OECD) countries. The integrated entropy–CoCoSo approach for evaluating the sustainability of road transportation systems is introduced, and the framework process is proposed. The entropy method defines the weight of the decision criteria based on the real data. The advantage of the entropy method is that it reduces the subjective impact of decision-makers and increases objectivity. The CoCoSo method is applied for ranking the road transportation sustainability performance of OECD countries. Our findings revealed the top three countries’ sustainability performance: Japan, Germany, and France. These are countries with developed infrastructure and transportation services. Iceland, the United States, and Latvia were in the last rank among countries. This approach helps governments, decision-makers, or policyholders review current operation, benchmark the performance of other countries and devise new strategies for road transportation development to achieves better results.
TL;DR: In this article , the authors focused on evaluating the environmental efficiency for land transportation by using the data envelopment analysis (DEA) method with undesirable output to handle unwanted data, and the proposed model effectively determines the environment-efficient DMUs in a very time-efficient manner.
Abstract: The efficiency of land transportation contributes significantly to determining a country’s economic and environmental sustainability. The examination of land transportation efficiency encompasses performance and environmental efficiency to improve system performance and citizen satisfaction. Evaluating the efficiency of land transportation is a vital process to improve operation efficiency, decrease investment costs, save energy, reduce greenhouse gas emissions, and enhance environmental protection. There are many methods for measuring transportation efficiency, but few papers have used the input and output data to evaluate the ecological efficiency of land transportation. This research focuses on evaluating the environmental efficiency for land transportation by using the data envelopment analysis (DEA) method with undesirable output to handle unwanted data. By using this, the paper aims to measure the performance of land transportation in 25 Organization for Economic Co-operation and Development (OECD) countries in the period of 2015–2019, considered as 25 decision-making units (DMUs) in the model. For identifying the ranking of DMUs, four inputs (infrastructure investment and maintenance, length of transport routes, labor force, and energy consumption) are considered. At the same time, the outputs consist of freight transport and passenger transport as desirable outputs and carbon dioxide emission (CO2) as an undesirable output. The proposed model effectively determines the environment-efficient DMUs in a very time-efficient manner. Managerial implications of the study provide further insight into the investigated measures and offer recommendations for improving the environmental efficiency of land transportation in OECD countries.
••01 Nov 2018
TL;DR: Results indicate that the intermodal transportation model can reduce the total cost significantly when compared to the unimodal model.
Abstract: This paper presents a study on intermodal transportation network design problem. The problem is to minimize the total of fixed facility location cost, the transportation cost, the transfer cost, the emission cost, while at the same time, satisfies customer demand, the flow conservation over different transportation mode, the terminal capacity, the vehicle minimum utilization, and the percentage circuitry constraints. The mixed-integer programming model is developed and analyzed with data from the south of Vietnam. The transportation mode of consideration is truck and inland waterway. Results indicate that the intermodal transportation model can reduce the total cost significantly when compared to the unimodal model.
16 Apr 2021
TL;DR: A hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) is exploited to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs.
Abstract: With the effects of the COVID-19 pandemic, the e-commerce trend is driving faster, significantly impacting supply chains around the world. Thus, the importance of logistics and supply chain functions has been amplified in almost every business that ships physical goods. In Vietnam, the logistics service sector has seen rapid expansion. Since more and more businesses are seeking third-party logistics (3PL) providers to outsource the logistics functions, this article aims to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs. To this end, the authors exploit a hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) while examining the most influential and conflicting criteria regarding economic, service level, environmental, social, and risk aspects. Fuzzy information in the natural decision-making process is considered, linguistic variables are used to mitigate the uncertain levels in the criteria weights. First, FAHP (the weighting method) is adopted to evaluate and calculate each criterion’s relative significant fuzzy weight. FVIKOR (the compromised ranking method) is then used to rank the alternatives. The combination of FAHP and FVIKOR methods provides more accurate ranking results. As a result, reliability and delivery time, voice of customer, logistics cost, network management, and quality of service are the most impactful factors to the logistics outsourcing problem. Eventually, the optimized 3PLs were determined that fully meet the criteria of sustainable development. The developed integrated model offers the complete and robust 3PLs evaluation and selection process and can also be a powerful decision support tool for other industries.
01 Mar 2021
TL;DR: In this article, a decision support system is developed to assist businesses in the selection and evaluation of different 3PLLPs by a hybrid fuzzy multicriteria decision-making approach, where relevant criteria concerning the economic, environmental, social, and risk factors are incorporated and taken into the models.
Abstract: On the heels of the online shopping boom during the Covid-19 pandemic, the electronic commerce (e-commerce) surge has many businesses facing an influx in product returns. Thus, relevant companies must implement robust reverse logistics strategies to reflect the increased importance of the capability. Reverse logistics also plays a radical role in any business’s sustainable development as a process of reusing, remanufacturing, and redistributing products. Within this context, outsourcing to a third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies for today’s organizations, especially e-commerce players. The objective of this study is to develop a decision support system to assist businesses in the selection and evaluation of different 3PRLPs by a hybrid fuzzy multicriteria decision-making (MCDM) approach. Relevant criteria concerning the economic, environmental, social, and risk factors are incorporated and taken into the models. For obtaining more scientific and accurate ranking results, linguistic terms are adopted to reduce fuzziness and uncertainties of criteria weights in the natural decision-making process. The fuzzy analytic hierarchy process (FAHP) is applied to measure the criteria’s relative significance over the evaluation process. The fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS) is then used to rank the alternatives. The prescribed method was adopted for solving a case study on the 3PRLP selection for an online merchant in Vietnam. As a result, the most compatible 3PRLP was determined. The study also indicated that “lead time,” “customer’s voice,” “cost,” “delivery and service,” and “quality” are the most dominant drivers when selecting 3PLRLs. This study aims to provide a more complete and robust evaluation process to e-commerce businesses and any organization that deals with supply chain management in determining the optimized reverse logistics partners.
31 Mar 2021
TL;DR: A hybrid data envelopment analysis model that combines the DEA Malmquist method and the epsilon-based measure (EBM) for the first time to address the issue of performance evaluation of seaport terminal operators is presented.
Abstract: Today, over 80% of global trade is seaborne. In a world of global supply chains and complex industrial development processes, seaports and port operators play an integral role of utmost importance and act as an incentive to the development of the marine economy and particularly, the national economy in general. Most importantly, the supply chain and demand shocks of Covid-19 on container ports and the container shipping industry have intensified competition among terminal operators. Thus, it is imperative that managers evaluate competitiveness by measuring their past and current performance efficiency indexes. In so doing, we present a hybrid data envelopment analysis (DEA) model that combines the DEA Malmquist method and the epsilon-based measure (EBM) for the first time to address the issue of performance evaluation of seaport terminal operators. The applicability of the proposed hybrid approach is illustrated with a case study of the top 14 seaport companies in Vietnam. First, the Malmquist model is used to assess the total productivity growth rates of the companies, and its decomposition into technical efficiency change (catch-up) and technological investment (frontier-shift). Second, the EBM model is used to calculate the efficiency and inefficiency score of each company. Besides indicating the best-performing companies from certain aspects during the research period (2015–2020), the results reflect that the gap of applying the EBM method in the field of the maritime industry was successfully addressed, and together with the Malmquist model, the integrated framework can be an effective and equitable evaluation model for any area. Furthermore, the managerial implication provides a useful guideline for practitioners in the maritime sector in improving their operational efficacy and helps customers in selecting the best seaport companies in the outsourcing strategy.
14 Feb 2021
TL;DR: This research develops a multi-objective mathematical model to design four-echelon intermodal multi-product perishable supply chain configuration in order to ensure a balance of the three pillars of sustainable development: economy, environment, and society.
Abstract: Supply chain network design problem is increasingly showing its importance, especially the perishable supply chain. This research develops a multi-objective mathematical model to design four-echelon intermodal multi-product perishable supply chain configuration in order to ensure a balance of the three pillars of sustainable development: economy, environment, and society. The optimization objective functions of the model are, respectively, minimizing costs, delivery time, emissions, and the supply-demand mismatch in time. The model addresses particular problems in the supply chain of fresh fruits, which is more challenging compared to other types of perishable products due to its seasonal characteristics. The study proposes a new approach that combines and standardizes the above objective functions into a single weighted objective function. The solution from the model supports the decision-making process at both strategic and tactical levels. Strategically, the model supports decisions about the location, size of facilities, product flows, and workforce level. Tactically, the decision variables provide information on harvest time, delivery time, the delivery route, and mode of transport. To demonstrate its practical applicability, the model is applied to Mekong Delta region, Vietnam, where a variety of fruit types, large yields, and high distribution demand in this region make designing a shared supply chain desirable for its overall economic, environmental, and social concerns. Moreover, sensitivity analysis regarding weights of different objectives is performed to assess possible changes in supply chain configurations. Application of this model to other perishable products, the addition of modes of transport, social policy, and uncertainty parameters may be suggested for future research.
TL;DR: The integrated simulation modeling and response surface methodology is presented to solve an order planning problem in the construction supply chain and could be applied as a useful reference for decision-makers, purchasing managers, and warehouse managers to obtain the most suitable order policy for a robust order planning process.
Abstract: For building material distributors, order planning is a key process as a result of the increase in construction projects’ scale and complexity. In this paper, the integration of simulation modeling and the response surface methodology (RSM) is presented to solve an order planning problem in the construction supply chain. The interactions of various factors are examined to observe their effects on key system measurements, and a combination of factor levels is determined to achieve the optimal performance. RSM is applied to find the possible values of the optimal setting for system responses, which consists of three main steps: central composite design (CCD), Box–Behnken design (BBD), and a comparison of both designs. The model is tested with a realistic case study of a building material distributor in Vietnam to demonstrate its effectiveness. Controllable factors (independent variables), which are the review period (T), order quantity (Q), and safety stock (SS), are found to significantly affect system responses, which are the total cost (TC) and customer service level (CSL). The results provide the best settings of factor levels that produce the possible minimum TC and maximum CSL. The developed framework could be applied as a useful reference for decision-makers, purchasing managers, and warehouse managers to obtain the most suitable order policy for a robust order planning process.