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In a general case, container ship serves many different ports on each voyage. A stowage planning for container ship made at one port must take aceount of the influence on subsequent ports. So the complexity of stowage planning problem increases due to its muhi-ports nature. This problem is NP-hard problem. In order to reduce the computational complexity, the proble,n is decomposed into two sub-problems in this paper. Fi,'st, container ship stowage problem (CSSP) is regarded as "packing problem", ship-bays on the board of vessel are regarded as bins, the number of slots at each bay are taken as capacities of bins, and eontainers with different charaeteristics (homogeneous containez~ group) are treated as items packed. At this stage, there are two objective functions, one is to minimize the number of hays packed by containers and the other is to minimize the number of overstows. Secondly, containers assigned to each bays at first stage are alhs~ate to special slot, the objective functions are to minimize the metacentric height, heel and ove,'stows.The taboo search heuristics algorithm are used to solve the subproblem. The main focus of this paper is on the first subproblem. A ease certifies the feasibility of the model and algorithm.

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It is very. difficuh to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms (GAs). In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling.