| dc.description.abstract | The Telecommunications market has many competitor in Taiwan, result in profits decline. The carrier in order to provide customized services for “Key Account and Small Medium Enterprise Customers”, these carrier create a “one-stop-shopping” Selling model, it also call “Total Solution”. Total Solution must integrate a number of business partners for related implement services, and they can provide the best solution to the customer. The purpose of this thesis that can select best partners after carrier obtain customer official orders, and focus the construction project improve a shortest implement time and the lowest labor costs, and according to the project scheduling to steps by steps implement and build these engineering.
The Thesis is based on the concept of Swarm Intelligence, it call “Particle Swarm Optimization (PSO)” Algorithm. PSO Algorithm contains rapid convergence characteristics. In recent years, it is a swarm intelligence algorithm for applied to solve some optimization question. PSO emphasis on inter-particle communication and it has some advantage, for example, low parameters setting, fast to search and feasibility of high-speed, etc. Now it has many scholars that has been published with PSO related improvement algorithms associated with such a practical application.
The thesis was divided into three parts; the first part of the first to introduce the concept of swarm intelligence and then introduce more popular optimization algorithm at present in several academic organization, and based on PSO optimization algorithm to do a simple comparison algorithm with others. The second part, we will focus on basic concept of the PSO and all kind of the improvement PSO algorithm description its further concepts and variety. The third part is the combination of the use of improved PSO concept and fuzzy decision-making, according to Total Solution executing partner election and total cost ownership optimization after the carrier get the orders, and use values of multi status to proof PSO/FD can be made more efficient partner selection of the optimal solution to the problem, and then we used PSO combine “Job-shop Scheduling Problem(JSP)” strategies for the project during construction period, to optimize the scheduling in order to shortest the construction period, and it can achieve cost savings. Final chapter we can propose some conclusions and face to further improvement PSO, and propose future study and some related research suggestions.
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