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Proper tracking of progress remains a vital part of modern project management, defining prospects of successfulimplementation of planned tasks. There are several popular concepts of project monitoring, such as logicalframework approach (LFA), earned value management (EVM), etc., and each of them depends on properlyoptimized network graph that represents dependences between project tasks. Article describes the features andproblems of multi-objective optimization in project management with reference to network graphs. Thesignificant role of network graph optimization for project monitoring systems is proved and the model ofmulti-objective optimization of the network graph on criterion functions of duration and project cost based onNSGA-II genetic algorithm is proposed as the main purpose of research. Model takes into account the reservesof time on a critical way of the network graph, possibility of decreasing the load of available resources at theexpense of time reserves on non-critical ways of the network graph, variety of used resources and options ofdelegation. One of its main advantages is quite low laboriousness of implementation, that depends on number ofnodes on the network graph of the project and on number of possible options of delegation for the project taskswith several alternatives of delegation. Model has been tested on sample project with real data and results havebeen analyzed.

Genetic Algorithm of Network Graph Multi-Objective Optimization as an Instrument of Project Monitoring