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In a demand driven market, optimal allocation of capacity to the demand has been one of the major issues. In this paper, we consider a single global freight firm allocating its capacity to its own regional sales offices. The firm sells cargo space based on two types of contracts: long-term and spot sales. Regional sales offices utilize their effort...
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... Firstly, many existing approaches may not adequately account for the dynamic and volatile nature of modern production environments [17]. Rapid changes in demand, disruptions in the supply chain, or unexpected machine failures pose challenges that traditional optimization models may struggle to address effectively [18]. Additionally, the majority of optimization methods may not fully exploit the potential benefits of real-time data and Industry 4.0 technologies, limiting their adaptability and responsiveness [19]. ...
This paper addresses the need for innovative optimization solutions in automotive manufacturing. Through advanced algorithms, we review existing methods and introduce novel approaches tailored to this sector. Our literature review identifies gaps and limitations in current methodologies. We define a specific optimization problem within automotive manufacturing, emphasizing its unique challenges. Our key contributions include: (a) Exploring hybrid optimization algorithms, combining genetic algorithms with simulated annealing for a 15% improvement in convergence speed, (b) Integrating machine learning techniques, resulting in a 20% reduction in optimization error compared to static settings, (c) Incorporating multiobjective optimization, achieving a 25% improvement in simultaneous cost and efficiency optimization, and (d) Proposing dynamic optimization algorithms, reducing decision-making latency by 30% during rapid environmental changes. Case studies demonstrate practical application, with quantitative results highlighting the superiority of our approaches over traditional methods. Additionally, the data analysis was conducted using Python, contributing to the robustness and accuracy of our findings.
... The initial research area of digital transformation lies in enterprises, and digital transformation is a form of change based on digital technology to support the development and operation of enterprises [14][15][16]. Digital transformation is characterized by platform and openness and belongs to the change of traditional organizational forms [17][18][19]. ...
The profound impact of the digital transformation and upgrading of China’s manufacturing industry on the global supply chain forms the core of this analysis. This paper introduces a measurement model for assessing the manufacturing digital transformation and upgrading, which includes constructing an indicator system and calculating the weights of these indicators using the entropy value method. Subsequently, the raw data for each indicator are processed through the maximum-minimum value method. Furthermore, this study advances a global supply chain performance assessment SCOR model tailored to the specifics of manufacturing digital transformation and upgrading. It conducts a quantitative analysis of key indicators, typically challenging to quantify, thus deriving their numerical expressions and examining the effects of performance changes. In 2023, China’s comprehensive index for transformation and upgrading escalated to 83.84%, a significant increase from 6.78% in 1999. In a simulation experiment focusing on the integrated circuit manufacturing industry, the digital transformation and upgrading of China’s manufacturing sector is shown to enhance production inventory levels within the global supply chain and reduce delivery times. The Estimated Lead Time (ELT) service level improved by 5%, reaching 100%. At the same time, revenues and profits saw increments of approximately 44.66 million and 32.11 million US dollars, respectively, relative to scenarios absent of such digital advancements.
... In the global community, there is a trend towards integration, development of a unified complex of the world economy functioning, joint solution of most economic problems and creation of a single market space [1]. This trend is complemented by another development, the regionalization of the world and its multipolarity, which manifests in a redistribution of regulation and the role of individual countries and groups of countries in the world economy [2]. ...
It is found that regions with depleted, or on the verge of depletion, of mineral resources are subject to additional pressures due to intensifying social and environmental problems. This paper proposes the development of the mining industry, reducing the dependence of the economy on the sharp volatility of the raw materials market in a period of global shocks by addressing social and environmental problems in regions with a depleting mineral resource base. It is assumed that the geotechnology development from simple mineral extraction to technologies providing a full cycle of georesources development with industrial waste recycling contributes to the resource provision of sustainable development. The material and mineralogical composition of the four tailing dumps (Uchalinskiy, Buribayskiy, Sibayskiy and Gaiskiy Ore-Processing plants have been studied) united with the similarity of the processed raw materials, and as a consequence, the similar enrichment technology has been studied and established. An approximate estimate of valuable components left in industrial wastes was made. The possibility of valuable component extraction (e.g., gold) from tailings using double agitation cyanidation was substantiated. There is no necessity of obligatory grinding of tailings to increase the recovery rate of valuable components. It was experimentally determined that the extraction of gold from tailings is 75.9–82.14% and depends on the investigated technogenic raw material. It has been proved that industrial waste can be recycled for the purpose of the resource provision of sustainable development. The need for further, more detailed studies of industrial formations has been identified. This will help to identify patterns of valuable component distribution in the industrial mass and to study its extraction possibilities in more details.
... Cárdenas-Barrón and Sana [37] studied an EOQ inventory model where demand is dependent on the marketing efforts. Kim and Chung [38] investigated the most effective capacity allocation strategy for a freight firm with regional sales offices. ...
The sustainable EPQ models that have been proposed in the inventory literature are insufficient to address the practical scenario of defects in manufacturing and subsequent rework for remedial actions. In this article, sustainable inventory model with rework for the faulty products has been studied. Promotional activities are the key factors that significantly affect the market demand for an item. The impacts of random defects and combining economic and environmental elements on the economic order quantity with price and promotional effort dependent demand have been addressed. Numerical illustrations along with sensitivity analysis are presented to reveal the relevancy as well as computational tractability of the proposed investigation. For the profit optimization, a mixed integer problem has been formulated and analyzed by using Bat metaheuristic optimization algorithm.
