油价下跌的根本原因和深远影响

上世纪后半期以来,世界油价变化已经历了4个阶段:第一阶段为二战后到1973年平稳的特低油价期,第二阶段为以两次石油危机为主体的油价剧烈动荡期,第三阶段为1986~1999年起伏的较低油价期,第四阶段为2000~2013年剧烈起伏的高油价期。此次油价下跌意味着进入了第五阶段——动荡中的油价较低期。它起因于国际石油市场供大于需的积累,雄厚的剩余产能和过量的石油储备是其两个明显标志;肇发于以沙特为首的海合会国家不愿看到自己的市场份额被侵占而不再减产保价,同时又叠加了世界经济疲软、美元指数走高的市场形势影响。市场供需将在新的低油价下达到新的平衡。低油价将首先对"财政油价"高且国内经济低迷的石油输出国产生强烈冲击,也将影响到生产成本低的石油输出国;而对石油消费国则是利大于弊,并将促进世界经济的回升;对于一些高成本的油气生产也会产生明显影响,最终将促使世界石油市场格局发生重大变化。低油价期的再次出现,还会使以化石能源为主体的时代比某些人预期的要长,但这也为多种新能源的发展争取了时间,从而使其更从容更健康地走向成熟。     

Using Computational Intelligence Algorithms to Solve the Coalition Structure Generation Problem in Coalitional Skill Games

Coalitional skill games (CSGs) are a simple model of cooperation in an uncertain environment where each agent has a set of skills that are required to accomplish a variety of tasks and each task requires a set of skills to be completed, but each skill is very hard to be quantified and can only be qualitatively expressed. Thus far, many computational questions surrounding CSGs have been studied. However, to the best of our knowledge, the coalition structure generation problem (CSGP), as a central issue of CSGs, is extremely challenging and has not been well solved. To this end, two different computational intelligence algorithms are herein evaluated: binary particle swarm optimization (BPSO) and binary differential evolution (BDE). In particular, we develop the two stochastic search algorithms with two-dimensional binary encoding and corresponding heuristic for individual repairs. After that, we discuss some fundamental properties of the proposed heuristic. Finally, we compare the improved BPSO and BDE with the state-of-the-art algorithms for solving CSGP in CSGs. The experimental results show that our algorithms can find the same near optimal solutions with the existing approaches but take extremely short time, especially under the large problem size.