The Generalized Transportation Problem is a variant of the classical Transpor-tation Problem, where the sum of the amounts of goods delivered to the destina-tion points is different from (usually lower than) the total amount sent from the sources. The Stochastic Generalized Transportation Problem (SGTP) is a version with random demand. We present the Bi-Criteria SGTP and propose an algorithm for determining the set of effective solutions.
Planning is one of the most important aspects of project management. A project plan defines objectives, activities and timeframe for project realization. To be able to define the required timeframe for project realization it is important to prepare its schedule. The purpose of this paper is to present the project scheduling problem as a multiple criteria decision making problem and to solve it using two evolutionary algorithms: SPEA2 and an evolutionary algorithm driven by the fuzzification of Pareto dominance. A comparison of these two approaches is conducted to investigate if it is reasonable to use the fuzzification of the Pareto dominance relation in evolutionary algorithms for the multiple criteria project scheduling problem
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