Minimizing the normalized sum of square for workload deviations on m parallel processors

In many organizations, it is desirable to distribute workload as equally as possible among a group of employees or machines. This paper proposes a performance measure, that we call the Normalized Sum of Square for Workload Deviations (NSSWD), and studies the problem of how to schedule a set of n jobs on m parallel identical processors in order to minimize the NSSWD. The NSSWD criterion is relevant where uniformity of wear to machines or of workload to employees is desirable. An algorithm, called Workload Balancing (WB), is proposed for solving this problem. Moreover, we perform a simulation experiment to evaluate WB against several well-known heuristics in the literature. Lastly, we discuss the computational results obtained from the simulation experiment.