Software Project Scheduling Problem is one of the most crucial issues in software development because it includes resources planning; cost estimates, staffing and cost control which if not properly planned affect the timely completion of the software project. Software project scheduling is a problem of scheduling the tasks (work packages) and employees in such a way that the overall project completion time is minimized without violating dependency constraints (tasks dependencies) and being consistent with resource constraints. This study adopts a Search Based Software Engineering approach that focuses on multi-objective optimization for a software project planning using the Shuffled Frog Leaping Algorithm, a memetic meta-heuristic algorithm. The objectives are optimal ordering of work packages without dependency violation and allocation of staff to the work packages such that only employee(s) with required competence(s) are allotted to a given work package. The study was carried out in four stages, namely: frog (solution) representation, definition of the fitness function, implementation of Shuffled Frog Leaping Algorithm and evaluation with a randomly generated Software Project Scheduling Problem. The study concludes that it is possible to find an efficient solution to a Software Project Scheduling Problem by implementing the SFLA than any other traditional computing means which are tedious, error prone and costly. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.