Unstable Desires

According to World Wide Web inventor Tim Berners-Lee, good page addresses should never change. Short URLs which hide complex programming code from the page address are good for webpage visitors. Please take a few minutes to devise a stable URL structure for your website before getting started, to reduce problems later. This tool can help you generate the Short URL configuration needed for your wiki. After you’ve installed your wiki paste a url from the wiki into the form below. Our tool will examine the url structure of your wiki and what software you are running then take a guess of what article path you may want and then give you the configuration for that short url setup. At that point you’ll have the option to change the article path and fine tune any issues in the detected software setup. Before you go on, do make sure you haven’t made a key mistake when you installed your wiki. Many people want /wiki/Article style urls like Wikipedia does and so they install their wiki at /{DOCUMENT_ROOT}/wiki/ this is incorrect. Wikis that use /wiki/Article style urls have their MediaWiki installation setup at /{DOCUMENT_ROOT}/w/ or /{DOCUMENT_ROOT}/ and setup short urls for /wiki/Article.

For mediawiki experts.

Scheduling is a key factor for manufacturing productivity. In a manufacturing environment scheduling is that allocates machines for processing a number of jobs. Proper and effective scheduling can cut lead times, improve on-time delivery, reduce inventory, and increase the reputation of enterprise. Recently, with the competitive pressure of today’s global market and consumer demand for variety, scheduling problem is becoming more and more important for the manufacturing industry.It is well-known that the Job Shop Problem is NP-hard, and the minimum Makespan problem of Job Shop scheduling is a classical combinatorial optimization problem. However, our theoretical understanding of these combinatorial optimizations is very limited, leading to significant problems for both researchers and practitioners. Specifically, the lack of a theory of problem impedes the development of more effective algorithms, prevents practitioners from identifying the algorithm most appropriate for a given problem.Based on analyzing combinatorial optimization and the model of JSP, we perform a novel analysis of the fitness landscapes of the Job Shop problem, prove that the JSP problem is very complexity; we research the configuration space of the JSP, trying to find the inherent characteristics of the Job Shop problem. Those results can provide theoretical basis for solving JSP. And on the basis, we give the methods framework to solving JSP. Those may provide a partial explanation for the remarkable success of the latter in solving the JSP.First, we introduced the general research methods of combinatorial optimization and the No Free Lunch theorem, and studied the fitness landscape of the knapsack problem and traveling salesman problem, and analyzed the global search. Then the relationship between fitness and the factors of impact of the fitness landscape space were analyzed. Second, the mathematical model and disjunction were given, and the complexity of this model was analyzed, and the characters of the fitness were studied, including the factors of impact of the Job Shop problem’s fitness landscape space were analyzed, followed it show that the landscape of the JSP is non-regular. Then the relation between the backbone and the fitness of the JSP is studied.Third, in order to using the landscape characters of the Job Shop to solve the problem, we also discuss the characters of evolution algorithm. In the process solving combinatorial optimization, we research the principle of crossover processing and mutation processing, and how those can impact the global optima. We get three typical fitness landscapes of the Job Shop problem, and we develop a general, fast and easily implemented hybrid optimization algorithm which base on Job Shop Problem Fitness Landscape and the particle swarm optimization;The effectiveness and efficiency of the proposed algorithm are demonstrated by applying it to some benchmark Job Shop scheduling problems. The effectiveness of the hybrid optimization algorithm model is also validated. One scheduling tool DAPSOJSP is developed.Finally, conclusion is drawn and the future research focus is pointed out.

News

April 3^rd, 2012: After a long incubation period, a new generation of the VirtualLabs is emerging: EvoLudo, a wiki based system that facilitates collaborative efforts to complement and augment research articles on evolutionary dynamics with interactive tutorials.

As of today a new tutorial on the Stochastic dynamics in finite populations is available on EvoLudo complementing a research article with Arne Traulsen and Jens-Christian Claussen in Phys. Rev. E 85 041901 doi: 10.1103/PhysRevE.85.041901.

Some of the VirtualLabs tutorials have already been revised, extended and migrated to EvoLudo and the remaining ones will follow in the near future. If you would like to get involved please contact me.

The first version of the VirtualLabs has been published in 2002, while I was working as a post-doctoral fellow with Karl Sigmund. Over the ten years the VirtualLabs have attracted almost 300’000 visitors. Now let’s take this to a new level with EvoLudo.

The VirtualLabs will remain available but no further updates to this site are planned in the near future. Please update your links and take advantage of the new and much more powerful java applets on EvoLudo.

Comments and suggestions are welcome.

—>

The best part of book tours are the questions. After spending years with the same ideas and sentences – they become old friends – it’s invigorating to see how people react, to keep track of which concepts spark their curiosity. It’s also fun to consider questions that never occured to me while writing the book. For instance, I was recently stumped by a seemingly obvious query that I hadn’t really considered. It was asked by a 4th grader: “What,” he wanted to know, “is the downside of creativity? Isn’t it possible that humans are too creative?”

via wired.com