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Green manufacturing has become a new production mode for the development and operation of modern and future manufacturing industries. The flexible job shop scheduling problem (FJSP), as one of the key core problems in the field of green manufacturing process planning, has become a hot topic and a difficult issue in manufacturing production research...
Context in source publication
Context 1
... since the model in this study incorporates energy consumption as an index, additional data need to be generated and extended accordingly. Random data within a reasonable range were generated, and the corresponding values are presented in Table 3. The table includes transportation energy consumption and transportation time, which have been standardized to a unified dimension. ...Similar publications
Globally, the consumption of aquatic foods has experienced significant growth in recent decades, primarily propelled by the expansion of the aquaculture sector. This growth can be attributed to adopting more sustainable production practices, increased supply, and greater awareness of the health benefits of these foods. Aquatic foods represent a pot...
This study aims to determine and analyze the influence of social media marketing on impulsive purchases and hedonic shopping values and to analyze the role of impulsive purchase reactions that mediate hedonic shopping values. The target of this research is all online consumers in Bandung City aged between 18-25 years as many as 150 respondents. Sam...
The flexible job shop scheduling problem (FJSP), one of the core problems in the field of generative manufacturing process planning, has become a hotspot and a challenge in manufacturing production research. In this study, an improved self-learning genetic algorithm is proposed. The single mutation approach of the genetic algorithm was improved, wh...
Background
The objective of this bibliometric inquiry was to scrutinize domains that delve into the repercussions of the 2019 coronavirus disease (COVID-19) pandemic on individuals afflicted with autism spectrum disorder (ASD), worldwide scholarly findings of interrelated research, and forthcoming trajectories.
Methods
To conduct a literature anal...
This study utilizes Sentinel-2 satellite data, remote sensing time series data MOD13Q2, and daily meteorological data from the meteorological station in Weinan City, Shaanxi Province. The aim is to accurately extract winter wheat planting areas and construct a remote sensing index system that is highly correlated with winter wheat yield. The index...
Citations
Sand cat swarm optimization algorithm is a meta-heuristic algorithm created to replicate the hunting behavior observed by sand cats. The presented sand cat swarm optimization method (CWXSCSO) addresses the issues of low convergence precision and local optimality in the standard sand cat swarm optimization algorithm. It accomplished this through the utilization of elite decentralization and a crossbar approach. To begin with, a novel dynamic exponential factor is introduced. Furthermore, throughout the developmental phase, the approach of elite decentralization is incorporated to augment the capacity to transcend the confines of the local optimal. Ultimately, the crossover technique is employed to produce novel solutions and augment the algorithm's capacity to emerge from local space. The techniques were evaluated by performing a comparison with 15 benchmark functions. The CWXSCSO algorithm was compared with six advanced upgraded algorithms using CEC2019 and CEC2021. Statistical analysis, convergence analysis, and complexity analysis use statistics for assessing it. The CWXSCSO is employed to verify its efficacy in solving engineering difficulties by handling six traditional engineering optimization problems. The results demonstrate that the upgraded sand cat swarm optimization algorithm exhibits higher global optimization capability and demonstrates proficiency in dealing with real-world optimization applications.
