There is no term for pressure ( P∇V) in the first law of black hole thermodynamics. To address this question, we study the first law of black hole thermodynamics and derive an expression for it. We report that this pr...There is no term for pressure ( P∇V) in the first law of black hole thermodynamics. To address this question, we study the first law of black hole thermodynamics and derive an expression for it. We report that this pressure corresponds to the Hawking temperature and is inversely proportional to the quartic of the Schwarzschild radius. It implies that a lighter and smaller black hole exerts more pressure on its surrounding environment. It might shed light on the other thermodynamic aspects of the black hole.展开更多
Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been...Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.展开更多
Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).F...Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.展开更多
根据时空对称性,确定了整体单极Anti de Sitter(AdS)黑洞的事件视界和宇宙视界的位置,利用Damour Ruffini方法研究了AdS黑洞的温度,给出了Klein Gordon方程在视界附近的渐近解.通过引入Edding ton Finkelstein坐标,解波动方程所获得的热...根据时空对称性,确定了整体单极Anti de Sitter(AdS)黑洞的事件视界和宇宙视界的位置,利用Damour Ruffini方法研究了AdS黑洞的温度,给出了Klein Gordon方程在视界附近的渐近解.通过引入Edding ton Finkelstein坐标,解波动方程所获得的热谱,证实了AdS黑洞具有Hawking辐射.展开更多
文摘There is no term for pressure ( P∇V) in the first law of black hole thermodynamics. To address this question, we study the first law of black hole thermodynamics and derive an expression for it. We report that this pressure corresponds to the Hawking temperature and is inversely proportional to the quartic of the Schwarzschild radius. It implies that a lighter and smaller black hole exerts more pressure on its surrounding environment. It might shed light on the other thermodynamic aspects of the black hole.
文摘Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.
文摘Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.
文摘根据时空对称性,确定了整体单极Anti de Sitter(AdS)黑洞的事件视界和宇宙视界的位置,利用Damour Ruffini方法研究了AdS黑洞的温度,给出了Klein Gordon方程在视界附近的渐近解.通过引入Edding ton Finkelstein坐标,解波动方程所获得的热谱,证实了AdS黑洞具有Hawking辐射.
