Transportation problem is an optimization problem. In general, it was studied under random or uncertain condition. Considering the recent complexity, it is not enough to make should be a perfect transportation plan only based on. Usually, there is not only uncertainty but also randomness in many systems. In this paper, the aim is to investigate a transportation problem under uncertain and random environment. As a result, a conceptual uncertain random model is proposed for the problem, where the supplies are considered as random variables, and the costs and the demands are uncertain variables. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, transforming the model into a crisp mathematical form is the main conclusion. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, the above model can be turned to a mathematical form. Then transforming the model into a typical mathematical programming model is the main conclusion by using uncertainty theory and probability theory. At the end, a numerical example is given to show the feasibility of the model.

In the location science, environmental effect becomes a new main consideration for site selection. For the unwanted facility location selection, decision makers should consider the cost of resolving the environmental conflict. We introduced the negative influence cost for the facility which was inversely proportional to distance between the facility and residents. An unwanted facility location problem was suggested to minimize the sum of the negative influence cost and the transportation cost. The objective cost function was analyzed as nonlinear type and was neither convex nor concave. Three GRASP (Greedy Randomized adaptive Search Procedure) methods as like Random_GRASP, Epsilon_GRASP and GRID_GRASP were developed to solve the unwanted facility location problem. The Newton's method for nonlinear optimization problem was used for local search in GRASP. Experimental results showed that quality of solution of the GRID_GRASP was better than those of Random_GRASP and Epsilon_GRASP. The calculation time of Random_GRASP and Epsilon_GRASP were faster than that of Grid_GRASP.

The analytic hierarchy process is known as a useful tool for the group decision making methods. This tool has been area such as investment, R&D management, manufacturing, production and marketing. Typically, transportation problems have addressed by mathematical programming. In this paper, an optimal solution of transportation problem was determined by the analytic hierarchy process.

해양 석유 생산은 ‘해양‘이라는 특성에 기인하는 여러 가지 변수를 동반하면서 막대한 비용과 시간을 필요로 한다. 모든 관련된 프 로세스는 인명, 환경 그리고 재산의 손실을 줄이기 위한 치밀한 일련의 계획에 의하여 통제된다. 이 논문은 해양 석유 생산 및 수송의 최적화 문제를 다룬다. 문제 영역의 범위를 정의하기 위해 해양 석유 생산 및 수송 네트워크를 제시하고 그 문제를 해결하기 위한 혼합정수계획모형 을 구축하였다. 제안된 최적화 모형의 타당성을 확인하기 위해 가상의 해양 유전과 수요 시장을 바탕으로 MS Office Excel의 해찾기를 이용 하여 계산실험들을 수행하였다. 해양 석유 생산 및 수송 네트워크 하위 흐름은 해양 유전에서 생산된 원유를 수요 시장으로 배분하는 해사수 송문제가 된다. 이 해사수송문제를 해결하기 위해 집합 패킹 모형을 이용하여 구축된 MoDiSS(Model-based DSS in Ship Scheduling)를 사 용하였다. 이러한 연구결과들은 실제적인 해양 석유 생산 및 수송 최적화 문제에 의미 있게 적용될 수 있으리라 사료된다.