This paper develops an efficient variant of a Genetic Algorithm (GA) for a ship routing and scheduling problem (SRSP) with time-window in industrial shipping operation mode. This method addresses the problem of loading shipments for many customers using heterogeneous ships. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and ship capacities. The results of a computational investigation are presented and the solution quality and execution time are explored with respect to problem size. The proposed algorithm is compared, in terms of solution quality and computational time, with an exact method that uses Set Partitioning Problem (SPP). It is found that while the exact method solves small scale problem efficiently, treating large scale problems with the exact method becomes involved due to computational problem, a deficiency that the GA can encounter. Meantime, GA consistently returns better solution than other published work using Tabu Search method in term of solution quality.

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Web applications are used in academic institutions, such as universities, for variety of purposes. Since these web pages contain critical information, securing educational systems is as important as securing any banking system. It has been found that many academic institutions have not fully secured their web pages against some class of vulnerabilities. In this empirical study, these vulnerabilities are focused and their existences in the web sites of the academic institutions are shown. The degree of securing web pages in education systems is measured. The differences among academic institutions on protecting their web applications are discussed.Recommendation on ways of protecting websites is addressed.