AN INTEGRATED MILP FRAMEWORK FOR PROJECT SCHEDULING AND TIME-COST TRADE-OFF IN OIL AND GAS PROJECTS

Abstract

This study introduces an integrated optimization framework for project scheduling and time-cost trade-off analysis specifically tailored for oil and gas projects. In the real market, traditional planning tools use a work-based deterministic scheduling methodology. It has limitations when the work involves complex interactions among activity durations, resource constraints, and cost implications. To improve the handling strategy with these limitations, this research develops a mixed-integer linear programming (MILP) model that simultaneously optimizes project duration and total execution cost while incorporating constraints on activity crashing and resource availability. The model in this thesis is designed to be applied to a process that links precedence relationships, time-indexed activity scheduling, and resource allocation constraints to ensure realistic and feasible project execution. A weighted multi-objective formulation is used to balance the trade-off between minimizing project duration (makespan) and minimizing total costs. In addition, a layer of normalization is included to facilitate consistent comparisons across objectives and to generate a Pareto frontier that represents optimal trade-off solutions. The outcome framework is implemented in a real case study from the North Field Expansion Project in Qatar, where multiple scenarios were analyzed by adjusting the weighting parameter. The results indicate that early-stage activity crashing leads to significant reductions in project duration with relatively moderate cost increases. Nevertheless, further reductions may cause diminishing returns and substantial cost escalation. The generated trade-off curve provides decision-makers with valuable insights for selecting optimal scheduling strategies based on project priorities. The research adds value by presenting a practical and scalable optimization tool that enhances decision-making in complex project environments. The proposed approach can provide planners with better support in improving project execution efficiency by mathematically evaluating the effects of time-cost trade-offs within realistic operational constraints.

Date of Award	2026
Original language	American English
Awarding Institution	HBKU College of Science and Engineering