S
Saurabh Pratap
Researcher at Indian Institutes of Technology
Publications - 74
Citations - 1050
Saurabh Pratap is an academic researcher from Indian Institutes of Technology. The author has contributed to research in topics: Computer science & Supply chain. The author has an hindex of 13, co-authored 46 publications receiving 481 citations. Previous affiliations of Saurabh Pratap include University of Hong Kong & Indian Institute of Information Technology, Design and Manufacturing, Jabalpur.
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Developments in the aluminum metal matrix composites reinforced by micro/nano particles – A review:
TL;DR: In this paper, the micro/nano reinforced particle aluminum metal matrix composites (Al-MMCs) are widely used in manufacturing sector due to light-weight, superior strength-to-weight ratio, better fracture tough, and better fracture resilience.
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Optimal collaborative transportation service trading in B2B e-commerce logistics
TL;DR: The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm for less-than-truckload carrier collaboration decision-making in the e-commerce logistics network and illustrate that the higher degree of cooperation, the more benefits for carriers.
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A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach
TL;DR: A chemical reaction optimization algorithm is proposed to solve the problem in a large-scale realistic environment and compared with the results with block-based genetic algorithm, genetic algorithm and particle swarm optimization, which shows that the developed model achieves better utilization of port resources and available berths.
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Game theoretic analysis of horizontal carrier coordination with revenue sharing in E-commerce logistics
TL;DR: In this paper, it is proved the effectiveness of horizontal carrier collaboration and explicate the reason for the lower marginal profit in logistics theoretically.
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What attracts vehicle consumers’ buying
TL;DR: A novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation.