Multi-Objective Optimization of Labor Allocation in Surface Field Development Projects

Modern capital construction projects in the oil and gas industry are characterized by a high degree of complexity due to the multi-level structure of work, the significant duration of technological stages, and the strict dependence of task completion dates on available labor resources. In such conditions, traditional calendar and resource planning methods are insufficient to find a balance between the project’s duration and the amount of labor required, which requires the use of multi-criteria optimization methods. The purpose of this study is to develop and test an approach to optimizing the allocation of labor resources using the example of a project for the construction of SDFs. The methodological basis of the work is to use a Pareto optimization model for the composition of project teams, adapted to the company’s organizational and production structure. The Pareto front was obtained as a result of the computational experiments, reflecting compromise solutions between the duration of the project and the total labor costs, and 21 implementation scenarios were identified, of which 17 meet the customer’s time requirements. An analysis of the obtained scenarios showed that the proposed approach provides flexibility in choosing a strategy: from minimizing deadlines while increasing resource costs to optimizing labor costs while maintaining the allowable duration. The use of multi-criteria optimization methods makes it possible to reduce risks and improve the quality of management decisions in projects implemented using a cascade management model.

Allocation of labor resources; Calendar and network planning; Multi-objective optimization; Pareto optimization; Surface field development project

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