This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production ...This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production efficiency.The shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and sustainability.Nesting algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and hybrid.Exact algorithms ensure optimal solutions but are computationally demanding.In contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal outcomes.Metaheuristic algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational efficiency.Hybrid algorithms integrate the strengths of different approaches to further enhance performance.This review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational efficiency.The findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in shipbuilding.By adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall performance.Future research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.展开更多
A complex autonomous inventory coupled system is considered. It can take, for example, the form of a network of chemical or biochemical reactors, where the inventory interactions perform the recycling of by-products b...A complex autonomous inventory coupled system is considered. It can take, for example, the form of a network of chemical or biochemical reactors, where the inventory interactions perform the recycling of by-products between the subsystems. Because of the flexible subsystems interactions, each of them can be operated with their own periods utilizing advantageously their dynamic properties. A multifrequency second-order test generalizing the p-test for single systems is described. It can be used to decide which kind of the operation (the static one, the periodic one or the multiperiodic one) will intensify the productivity of a complex system. An illustrative example of the multiperiodic optimization of a complex chemical production system is presented.展开更多
Optimal capacity configuration(OCC)of large-scale energy bases with multi-timescale operation characteristics presents a critical challenge.To address the problem,this study proposes an OCC approach of large-scale ene...Optimal capacity configuration(OCC)of large-scale energy bases with multi-timescale operation characteristics presents a critical challenge.To address the problem,this study proposes an OCC approach of large-scale energy bases considering external multi-stochastic scenarios and interactive multi-timescale objectives.Firstly,guided by the system theory,the nonlinear state-space description is presented for systematic analysis of a general large-scale energy base.Due to interactive multi-timescale objectives between annual and daily cumulative objectives,a nested optimization structure is established.Then,considering the external multi-stochastic scenarios caused by the variables such as wind speed,solar irradiance,electric load,and thermal load,a multi-step optimization strategy is proposed including pre-configuration in regular scenarios and re-configuration by introducing micro-incremental scenarios.The multi-step optimization strategy and nested optimization structure jointly achieve the OCC of the large-scale energy base.In each step,the nested optimization structure is executed once.Finally,while ensuring the balance between thermal supply and load demand,the imbalances between electric power supply and the load demand are eliminated,significantly showing the efficiency of the proposed OCC approach.展开更多
文摘This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production efficiency.The shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and sustainability.Nesting algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and hybrid.Exact algorithms ensure optimal solutions but are computationally demanding.In contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal outcomes.Metaheuristic algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational efficiency.Hybrid algorithms integrate the strengths of different approaches to further enhance performance.This review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational efficiency.The findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in shipbuilding.By adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall performance.Future research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.
文摘A complex autonomous inventory coupled system is considered. It can take, for example, the form of a network of chemical or biochemical reactors, where the inventory interactions perform the recycling of by-products between the subsystems. Because of the flexible subsystems interactions, each of them can be operated with their own periods utilizing advantageously their dynamic properties. A multifrequency second-order test generalizing the p-test for single systems is described. It can be used to decide which kind of the operation (the static one, the periodic one or the multiperiodic one) will intensify the productivity of a complex system. An illustrative example of the multiperiodic optimization of a complex chemical production system is presented.
基金supported by the National Key R&D Program of China(No.2021YFE0102400)the National Natural Science Foundation of China(No.51906064).
文摘Optimal capacity configuration(OCC)of large-scale energy bases with multi-timescale operation characteristics presents a critical challenge.To address the problem,this study proposes an OCC approach of large-scale energy bases considering external multi-stochastic scenarios and interactive multi-timescale objectives.Firstly,guided by the system theory,the nonlinear state-space description is presented for systematic analysis of a general large-scale energy base.Due to interactive multi-timescale objectives between annual and daily cumulative objectives,a nested optimization structure is established.Then,considering the external multi-stochastic scenarios caused by the variables such as wind speed,solar irradiance,electric load,and thermal load,a multi-step optimization strategy is proposed including pre-configuration in regular scenarios and re-configuration by introducing micro-incremental scenarios.The multi-step optimization strategy and nested optimization structure jointly achieve the OCC of the large-scale energy base.In each step,the nested optimization structure is executed once.Finally,while ensuring the balance between thermal supply and load demand,the imbalances between electric power supply and the load demand are eliminated,significantly showing the efficiency of the proposed OCC approach.
