International Journal of Industrial Engineering: Theory, Applications and Practice
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Comparative Effectiveness of Data Normalization Methods in ARAS for Multi-Criteria Decision-Making Across Industrial Applications
Get PDFMulti-criteria decision-making (MCDM) utilizes various tools and methods to enhance decision-making across fields such as engineering, materials, manufacturing, and management. Data normalization is a crucial step in MCDM for converting criteria values to a standard scale, enabling accurate rating and ranking of alternatives. Selecting the appropriate data normalization method from various available options remains challenging yet crucial for effective decision-making across industrial applications. In this study, ten data normalization methods (DNMs) are evaluated with the ARAS (Additive Ratio Assessment) method, and their selection for enhancing robustness in MCDM is investigated. The suitability of each DNM is assessed through various test cases and sensitivity analyses, examining the impact of normalization on decision-making results. A comparative analysis of DNMs is performed using Spearman’s rank correlation, criteria weight variations, dynamic matrices, and plurality voting to identify the most effective data normalization methods. The findings from this study offer comprehensive insights into how different DNMs influence the performance of the ARAS method, providing practical guidance for improving decision-making accuracy across industrial applications. Through this process, four additional DNMs are identified as suitable for integration with the ARAS method, expanding its application scope beyond the traditional sum-based linear normalization method
Evaluation of Container Terminal Performance with Capacity Constraint Using System Dynamics
Get PDFContainer terminal ports are essential in supporting a country's logistics performance. Thus, it is necessary to improve the port's operation to increase its effectiveness. Port operations involve a lot of stakeholders and variables within the system that require all supporting components to be analysed, so a systemic approach is needed. This study investigates an effective decision to improve the performance of container port operations that utilize the system dynamics methodology. Port logistics performance is represented by the leading indicators of port service (service time and stacking yard usage). The results indicate that gate-out rates of container import flow and inaccurate information sharing related to container stacking systems impact port berthing time and yard occupancy ratio
Optimization Design of Fresh Cold Chain Logistics Network for Carbon Footprint
No full textWith the upgrading of consumption, the public demand for cold chain products and quality requirements is getting higher and higher, which promotes the rapid development of China’s cold chain logistics industry. As a transportation business with high energy consumption and high carbon emissions, cold chain logistics makes enterprises face high-cost pressure. Also, it contradicts the current low-carbon economy advocated by society. In order to balance the economic benefits brought by the rapid development of cold chain logistics and the negative impact on the environment, this paper constructs a multi-objective model with the lowest network construction cost and carbon emission as the objective function based on the customer demand in the region and designs a genetic algorithm with local search to solve the model. Simultaneously optimizing the distribution center location and distribution plan, the construction cost and carbon emission of the cold chain logistics network can be reduced to save costs and improve economic benefits. At the same time, the economic and social benefits are taken into account, which can provide a scientific decision-making basis for the network construction and operation of enterprises with cold chain logistics demands and contribute to the sustainable development of cold chain logistics
A Tripartite Evolutionary Game Analysis on The Co-construction of Fresh Food Supply Chain System with Blockchain Technology
No full textEliminating Information asymmetry and food safety risks in the fresh food supply chain with the help of blockchain technology has become one of the hot topics in academic and agricultural fields. However, as the non-rational stakeholders in the fresh food supply chain, ensuring that the three parties can actively participate in the construction of the blockchain system is a complex problem. This paper constructs a tripartite evolutionary game model among the cooperative(farmers), fresh food retailers, and third-party logistics providers, and then obtains the replicator dynamics function of stakeholders and analyzes the evolution trend in the co-construction of the fresh food supply chain system with blockchain technology. The results show that three Evolutionary Stable Strategies (ESS) are accepted by three players under specific parameters, and the equilibrium point remains stable under external interference. Moreover, the existence of an ideal cooperative state where all three players choose to participate actively has been confirmed. When blockchain systems generate additional benefits, they can incentivize active participation from stakeholders, and consumer attitudes toward traceable agricultural products actively correlate with these benefits. The blockchain protocol restricts participants, but excessively harsh penalties may inhibit sales and the involvement of third-party logistics (3PL)
A study of Optimal Assignment Model Considering Quality and Worker Level in Limited-Cycle with Multiple Periods For Smart Manufacturing
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In recent years, quality irregularities reported by various media have shaken public confidence in companies, impacting both sales and stock prices, even among global leaders in manufacturing. Additionally, the increase in foreign workers and variations in service length have introduced differences in worker skill levels. This study aims to identify optimal worker assignment strategies that balance quality and worker skill levels for efficient production. We propose an optimal assignment model for a smart production line in a limited-cycle, multi-period setting that considers both quality and due dates. Numerical experiments further analyze optimal arrangement strategies and characteristics across different worker skill levels
Metal Supply Chain Coordination with Revenue-sharing Contract: A Case Study in Khuzestan Steel Company
Get PDFThis paper aims to model a Metal Supply Chain to optimize the price and order quantity under decentralized and coordinated decision-making strategies in a two-level supplier-manufacturer chain. Modeling of this supply chain was performed concerning the leadership of one member and the following of another member using the Stackelberg game model. In this study, a revenue-sharing contract is used to create a coordination strategy in the steel supply chain, and sensitivity analysis on key variables is performed. The results of this research can help improve the profitability of the members in the MSC under a coordinated approach using a revenue-sharing contract compared to a decentralized one. The results of the sensitivity analysis demonstrated that with the increase in product quality, the total profit of the supply chain increases in both coordinated and decentralized modes, while the coordinated strategy yields a greater increase in total profit than the decentralized one
The Impact of Corporate Social Responsibility on Sustainable Development Performance - Mediating Effect of Dual Green Innovation
No full textGreen sustainable development remains the cornerstone of China's economic progress and the guiding principle for the transformation and advancement of its manufacturing sector. Aligned with China's objectives of achieving a "carbon peak" by 2030 and "carbon neutrality" by 2060, expediting the green development of manufacturing enterprises and enhancing their sustainable development performance are crucial to ensuring their long-term health and prosperity amid transformation and upgrading. This holds the key to realizing sustained and healthy growth for manufacturing enterprises as they navigate the process of transformation and advancement. According to stakeholder theory and natural resource-based theory, this study evaluates Chinese listed manufacturing enterprises, utilizing panel data spanning 2012-2021 to empirically analyze the relationship between CSR, dual green innovation, sustainable development performance, and redundant resources in these enterprises. A model is constructed to explain the effect of CSR on sustainable development performance. The findings demonstrate that CSR significantly cultivates both continuous and disruptive green innovation, elevating corporate sustainability performance. Continuous and disruptive green innovation represents positive mediating factors in this relationship. The moderating effect analysis indicates that non-sedimentary redundant resources exert a positive moderating effect between CSR and dual green innovation, while the moderating effect of sedimentary redundant resources between the two remains insignificant. Further exploration indicates that in the short term, continuous green innovation exhibits a more significant and positive effect on sustainability performance. Conversely, in the long run, disruptive green innovation demonstrates a greater positive effect on sustainability performance. Considering these conclusions and the specific characteristics and requirements of manufacturing enterprises, this paper proposes relevant recommendations to assist enterprises in effectively enhancing their sustainable development performance
Strategic Choices of Online Retailers in Live-Streaming E-Commerce
No full textSome online retailers, based on traditional channels, have launched live-streaming channels. To study the optimal live-streaming choices of online retailers, this paper models the supply chain composed of a manufacturer and an online retailer by establishing three modes: no live-streaming mode, influencer live-streaming mode, and retailer self-live-streaming mode. The online retailer's optimal choice of live-streaming mode is derived by analyzing the equilibrium solutions. The results suggest that when the sales ability of the employee-streamer and the live-streaming consumer purchase rate are high, it's always advantageous to opt for retailer self-live-streaming mode. Affected by the influencer's commission rate and fixed participation fee, the influencer live-streaming mode is harmful to the online retailer. However, if the influencer chooses a profit-sharing mechanism, the online retailer and influencer can achieve a Pareto profit improvement, and online retailers will open the influencer live-streaming mode
Impermanent Loss Mitigation for Decentralized Exchanges through Optimization
Get PDFDecentralized exchanges are one of the most remarkable revolutionary inventions in cryptocurrency trading. Decentralized exchanges present a way to set prices mathematically without maintaining the order book-based trading system. The order book-based trading system has been a widely-known method to determine prices in the stock markets and even in decentralized cryptocurrency exchanges for over 400 years. Recently, a new type of decentralized exchange has devised a constant function market maker to determine prices mathematically. Among them, the method of constant product market makers is the most widely used one. In addition, several constant function market makers have been proposed. However, there was little discussion about the desirable properties of a constant-function market maker regarding price and impermanent loss. In this paper, we discuss the desirable price and its effects on impermanent loss. This study considers two types of prices: the reference price and the actual price. We show that impermanent gain can be achievable under a certain condition and prove it mathematically. Two examples are provided to show that impermanent gain is achievable.
Topographic Maps of Brain Regions to Measure Human Trust in Automation
Get PDFAs complex automation increasingly enters the workplace, a human operator's trust affects the proper use of automation. This research aimed to identify stimulated brain regions using topographic maps to measure human trust in automation. Power spectrum analysis classified the frequency range, and coherence analysis identified functional connectivity within the brain regions. The results showed that the frontal lobe in the alpha and beta waves had strong connectivity in the trust situation. In contrast, the temporal lobe in the gamma waves had strong connectivity in the mistrust situation. These findings can contribute to monitoring human operators' trust in automation in uncertain or urgent situations and designing complex automation by calibrating human trust consistent with the automation abilities in the industry