Advances in Industrial Engineering

The increasing recognition of the circular economy (CE) as a sustainable business model has spurred significant research and application across various industries. This study aims to provide a comprehensive analysis of the intersection between circular economy and sustainability, analyzing the evolving trends, key challenges, and opportunities within this domain. Through a content analysis of 112 scholarly articles published between 2022 and 2024, we delve into the fundamental components of CE and sustainability, examining their interdependencies and potential synergies. Our analysis reveals that the circular economy and sustainability are deeply interconnected, both striving for a more sustainable future. The circular economy focuses on extending the lifespan of products through strategies like design for the environment, eco-innovation, sharing economy, product lifecycle extension, recycling, upcycling, and bioeconomy. Sustainability, on the other hand, seeks a balance between environmental, social, and economic factors. Both concepts share common goals of resource efficiency, reduced pollution, social equity, and innovation. By working together, they can create a more resilient and equitable world, minimizing waste, conserving resources, and ensuring a healthier planet for future generations.

Marine transportation has become a vital element of global trade, connecting commercial hubs around the world via low-cost sea routes. Its impact is increased by the environmental concerns raised by the associated maritime traffic, which necessitates a comprehensive and efficient method to resolving these worries. A vessel follows a predefined course and departs from the home port on a scheduled basis in order to reach its destination. It carries out loading and unloading operations at the allocated berth and crane during the tour. In order to conserve schedule, the vessel needs to navigate the route at the optimal speed, which is influenced by a number of factors including fuel consumption and vessel weight. This study used a novel model to generate a vessel schedule and route map for Iran's Shahid Rajaei Port in the Persian Gulf. The data suggest that the port can manage ten vessels at a time and has two cranes for loading and unloading each vessel. In addition, we carried out a sensitivity analysis on key components of our proposed model, including fuel costs, vessel weight, load-carrying capacity, and arrival/departure delays. The keys findings are as: higher arrival/departure costs result in shorter delays; higher fuel costs have a negative impact on the objective function; lower vessel weight results in better fuel efficiency; and higher vessel load-carrying capacity is coupled with higher fuel costs.

At present, electric vehicles (EVs) are increasingly recognized as a viable alternative to conventional internal combustion engine vehicles, primarily due to their superior environmental sustainability, particularly regarding carbon emissions, and their cost-effectiveness attributed to lower energy consumption. Consequently, the market share of electric vehicles has witnessed substantial growth in recent years, which has in turn heightened the demand for charging infrastructure. Conversely, the rising number of electric vehicles necessitating recharging-especially during peak demand periods- poses challenges such as prolonged waiting times at public charging stations and increased strain on the power distribution network. To address these issues and enhance network efficiency, the concept of Mobile Charging Stations (MCS) has emerged, offering flexible charging solutions in terms of both time and location. This paper introduces an innovative approach for the allocation and deployment of MCSs in areas with high demand, aimed at alleviating the burden on public charging stations. A mathematical model grounded in the Location-or-Routing Problem (LoRP) has been formulated, employing various truck-based and van-based mobile charging stations to collaboratively service demand points near public charging facilities. This strategy seeks to attain various achievements, including the reduction of network load and waiting times at charging stations while simultaneously expanding coverage to improve customer satisfaction. Based on conducted experiments, a comprehensive evaluation and analysis of the proposed model demonstrate that the LoRP significantly outperforms traditional models in terms of both coverage and cost efficiency.

E-commerce plays a vital role in today’s economy, and website usability is crucial for attracting customers and achieving higher conversion rates. Process mining offers significant advantages in analyzing user behavior, providing insights into typical user paths and identifying deviations. This study aims to enhance the usability of e-commerce websites by leveraging user behavioral data and process mining tools. User behavioral data from a cosmetics e-commerce website were collected and preprocessed. Various metrics were established to evaluate usability, revealing low task completion rates and high bounce rates. Bottlenecks were identified where users faced delays, indicating areas for improvement. Recommendations included redirecting users who remove items from their cart to the homepage, suggesting similar products, and addressing payment page issues. These suggestions aim to improve user experience and increase conversion rates. Despite limitations, such as the lack of detailed data, this study demonstrates the potential of process mining tools in enhancing website usability

This study aims to develop a mathematical model for the pricing of fresh products in a ‎fruit supply chain network. Stakeholders in this issue include fruit suppliers, primary fruit fields ‎and markets, retailers, end customers, processing industries, and disposal centers. Fruits and ‎vegetables are considered super fresh products because their color and taste change over time, ‎leading to spoilage. This article focuses on pricing this category of products considering ‎freshness-dependent demand and pricing and models the flow among suppliers, retailers, ‎customers, processing industries, and disposals. This study examines the pricing of fresh products ‎supplied by suppliers, transported, sold by retailers, and eventually delivered to customers and ‎processing industries and disposals, and considers multiple periods. The developed model uses ‎mixed integer linear programming (MILP) to maximize total profit, including transportation, ‎wholesale, and inspection costs. A numerical example is provided to validate the proposed model ‎and offer managerial insights to the relevant industry. The results indicate that appropriate ‎pricing contributes to overall profit and increased sales. Lastly, sensitivity analysis demonstrates ‎the relationship between total profit, freshness, and product sales. A total profit model for ‎retailers is considered to optimize pricing based on optimal cost parameters.‎