Equitable Payment Distribution for Project-Expert Scheduling Using Genetic Algorithm

The human race is facing a large number of very complex real-world problems. One of them is a very common and typical problem faced by many large organizations executing multiple projects concurrently. They have a huge pool of similarly skilled human resource (experts) which needs to be allocated to multiple projects with different units of work and different payment rates such that each expert gets an equitable payment. The above problem is an allocation problem and it falls into the category of NP Hard problems. A simple and obvious approach could be application of Round robin technique to this problem. However, this technique is not suitable and has a set of limitations. As per no polynomial-time algorithm exists to solve this problem optimally. In this paper we have introduced a novel Genetic Algorithm based approach with problem specific three-dimensional representation scheme to find the optimal solution for the equitable payment distribution. We have implemented an algorithm that achieves average performance which is close to the optimal across many experimental scenarios. Furthermore, this evolutionary algorithm does not require special high powered computing hardware and is still quite efficient. This makes it ideally suitable for solving this type of allocation problems.