Projects in the Complex Engineer-to-order (ETO) sector are subjected to frequent schedule delays caused by engineering changes, supply chain delays and fabrication delays. Project organizations are faced with the challenge of realigning the project duration within the pre-determined time. Schedule delays often lead to 3-5% rise in project cost. This requires an efficient on-the-go reactive approach. At present, the development of strategy to realign the project is extensively manual in nature. This makes the exploration of alternative realigning strategies cumbersome. Lean Project Planning (LPP) and advances in Building Information Modelling (BIM) has enriched on-the-go planning. However, no existing tool equips the project organization to generate, visualize and evaluate possible set of alternative strategies in the event of a triggered change. No attention has been provided to integrate strategy generation algorithms like Evolutionary Algorithm with the LPP and BIM approaches. In this research, a tool was developed to enable the project organizations to generate and visualize strategies integrating Modified Evolutionary Algorithm (MEA) with LPP and BIM from a metaheuristic approach. Furthermore, by undertaking a case study on strategies adopted in real-life change events in a representative Complex ETO project, the reliability of the generated strategies was investigated. The application of the proposed tool in the real-life test case showed the advantages of having multiple alternative realignment strategies.