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In this paper, we propose a new concurrency control algorithm based on multi-agent systems which is an extension of majority protocol. Then, we suggest a clustering approach to get better results in reliability, decreasing message passing and algorithm’s runtime. Here, we consider n different transactions working on non-conflict data items. Considering execution efficiency of some different transactions simultaneously is one of our algorithm features. For evaluating performance of the proposed algorithm we applied it using the MPICH2 mechanism.

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We aimed to develop a mathematical method for planning, scheduling and increasing the productivity of projects with multiple goals, including reducing project time, resources, and negative cash flows, increasing floatiness of activities, and responding to the project's needs by considering various stakeholders and objectives. As such problems are NP-hard, particle swarm optimization was used to solve the multi-objective mathematical model. Then, the algorithm function was evaluated by changing the value of the parameters. We are looking for the use of multi-objective models for planning projects, which allow for planning each activity in different modes and functions using multiple objectives, enables project managers to implement their projects by considering various priorities. Based on previous studies on project schedules, it seems that most of them focus on reducing time and cost; nevertheless, this study intended to investigate issues like various operational modes of each activity, optimal and in-time allocation of resources, and to increase floatiness of activities.