The main significance of utilizing high-performance concrete as an effective item in the construction industry is the compressive strength assessment which requires a vast investigation of the design mix with calculat...
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The main significance of utilizing high-performance concrete as an effective item in the construction industry is the compressive strength assessment which requires a vast investigation of the design mix with calculated relevant compressive strength. Through the intelligence approaches, planning an accurate relationship between high-performance concrete different mix designs and their compressive strength is obtainable with the lowest cost of time and finance. Two models based on support vector regression methods are developed in this regard. The optimal output is calculated by tuning support vector regression key constraints by flow direction and biography-based optimization algorithm. The data set collected from the literature is divided into the training, and the testing phase, where the training data is used to develop the models, and the testing data is utilized to validate the accuracy of the models. The results showed a higher accuracy of the FDA_SVR method than the BBO_SVR method, with R-2 values of 0.9939 and 0.9755, respectively. moreover, the U95
Coordinating a supply chain necessitates a synchronization strategy for reordering products and a cost-effective production and replenishment cycle time. The aim of this paper is to present an optimization framework f...
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Coordinating a supply chain necessitates a synchronization strategy for reordering products and a cost-effective production and replenishment cycle time. The aim of this paper is to present an optimization framework for producing and distribution in the supply chains with a cooperating strategy. The main contribution of this paper is to integrate closed loop supply chain with open-shop manufacturing and economic lot and delivery scheduling problem (ELDSP). This integration is applied with the aim of better coordination between the members of the supply chain. This study examines the ELDSP for a multi-stage closed loop supply chain, where each product is returned to a manufacturing center at a constant rate of demand. The supply chain is also characterized by a sub-open-shop system for remanufacturing returned items. Common cycle time and multiplier policies is adopted to accomplish the desired synchronization. For this purpose, we developed a mathematical model in which a manufacturer with an open-shop system purchases raw materials from suppliers, converts them into final products, and sends them to package companies. Given that the ELDSPR is an NP-hard problem, a simulated annealing (SA) algorithm and a biography-basedoptimization (BBO) algorithm is developed. Two operational scenarios are formulated for the simulated annealing algorithm, after which both the algorithms are used to solve problems of different scales. The numerical results show that the biography-based optimization algorithm excellently performs in finding the best solution to the ELDSPR.
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