Objective: Balanced workload

Use the balanced workload objective to distribute work equally between resources.


The concept of balancing workload refers to the distribution of jobs among available resources in a way that ensures equitable allocation and efficient utilization of resources. It aims to prevent resource overloads or under utilization, promoting a harmonious and productive workflow.

Assigning weight to the balanced workload objective

By assigning a weight, you are indicating the importance of maintaining an even distribution of workload among resources. The optimizer will prioritize achieving a balanced workload, even if it means compromising other objectives to some extent, to adhere to the assigned weight.

For example, if the weight assigned to balanced workload is 80, and the weight assigned to preferred resources is 20, the optimizer will prioritize balancing workload over preferred resources.

Incompatible with minimize resources objective

Consider the following example:

A software development company, ABC Tech, that operates with a team of software engineers who work on multiple projects simultaneously. The company aims to optimize resource allocation and ensure a balanced workload among its engineers while keeping resource costs at a minimum.

If ABC Tech assigned a high weight to the objective of balancing workload, the resource scheduling optimizer will prioritize distributing tasks equally among the engineers, ensuring a balanced distribution of work. This can help prevent burnout, maintain productivity, and promote teamwork.

However, if the objective of minimizing resources was also given a weight, the optimizer will focus on reducing the number of resources involved in the scheduling process. This might result in a situation where a few highly skilled engineers are overloaded with work to minimize the overall number of resources utilized.

Assigning no weight to the balanced workload objective

When no weight is assigned to the workload balance objective, the optimizer has the flexibility to optimize scheduling outcomes without specific constraints related to workload distribution. It may focus on other objectives, without being bound by the requirement to balance workload.

This allows for more flexibility in achieving overall optimization, potentially resulting in imbalanced workloads if no specific weight is assigned to the objective.

Use case: Retail store staffing

Objective weighting:

  • Balance workload: 70%
  • Soft skills: 20%
  • Work priority: 10%

In a retail store, balancing workload is essential to ensure optimal customer service and maintain staff satisfaction. Soft skills gain importance for customer-facing roles. Work priority holds a lower weight as most retail tasks do not involve strict urgency constraints.