Optimizing Pharmaceutical Waste Collection Routes for Safe Disposal

Efficient route planning and optimization directly impact delivery costs, speed, and reliability, all crucial elements for staying competitive in the market. Here, we will examine several parameters that an optimization planner must consider. 

1. Custom Objective Equal Task Distribution

Custom Objective is a useful feature that allows users to pursue unique objectives that differ greatly from the typical approach of reducing travel costs. This feature enables users to customize the optimization method to achieve the following goals: 

• Reduce the number of cars utilized in the solution. 
  
  
• Reduce the time required to accomplish all jobs. 
  
  
• Distribute duties equally among all routes. 
  
  
• Distribute travel cost equally across all routes.
  
  

The above objectives can be utilized in conjunction with additional constraints such as vehicle prices, task duration limits, re-optimization, and other features provided by the Route Optimization Flexible API.

2. Re-optimization: New Tasks

NextBillion.ai’s Route Optimization Flexible API has an advanced re-optimization functionality that enables customers to re-optimize a collection of existing or new tasks by readjusting specific variables as needed. 

To re-optimize a routing plan, users must use the prior solution developed with the supplied restrictions at the time. To successfully add new orders/tasks to the re-optimized solution, users must determine whether or not to adjust the existing limitations of vehicle number, shift timings or capacity, task time frames, or any other factors.

Users are expected to rebuild the request to specify all of the new and current tasks. When a re-optimization request is received, the solver will attempt to include the additional tasks in the original solution with minimal modifications. In this manner, companies can quickly or at the last minute modify their route planning without having to make significant changes to their current plans.

3. Re-Optimization: Unassigned Tasks

The Route Optimization Flexible API from NextBillion.ai has strong re-optimization features that let users complete tasks that were not previously allocated by changing a few variables. The number of vehicles in the optimization request, the shift timings or capacity of the vehicles involved, the task time windows, or any other strategy that would raise the likelihood of receiving more tasks are examples of these variables.

Re-optimization relies on a previous solution that included certain unassigned tasks. Users are required to recreate the request and clearly describe the unassigned tasks. When the solver receives a re-optimization request, it will try to include the additional tasks in the original solution with minimal changes. This allows organizations to make rapid or last-minute updates to their route planning without having to make expensive changes to the existing plans.

4. Task Sequencing 

Relations are used to define the relationship between several tasks that should be completed in a specific order. NextBillion.ai’s Route Optimization Flexible API supports three sorts of relationships that customers can enforce: 

• in_same_route: All of the steps indicated in this sort of relation will occur on the same route. 
  
  
• in_sequence: All of the steps specified in this relation will occur within the provided sequence, but the optimizer may insert more steps if feasible. 
  
  
• in_direct_sequence: All the steps given in this relation will follow the provided sequence, with no further steps introduced between them by the solver.
  
  

However, a few points may be worth noting here. Relations are a difficult configuration, and the solution will not prioritize jobs, time_windows, soft constraint parameters, etc. Furthermore, while employing relations, the vehicle qualities such as capacity and abilities should be aligned with what the tasks on those relations require.

5. Vehicle’s Cost 

NextBillion.ai’s Route Optimization Flexible API currently supports two types of vehicle costs: fixed and per_hour. 

• Fixed costs: These are the costs of operating the vehicle, regardless of how long it is in use. Fixed costs include driver’s fees, licensing fees, and taxes. If only the fixed cost of the vehicle is specified, it will be added to the route’s travel costs. 
  
  
• per_hour: This method includes the hourly cost of operating a vehicle in optimization calculations. The optimizer will only consider the vehicle cost as the route’s overall cost if the vehicle’s per-hour cost is supplied. 
  
  

If fixed cost is also supplied, the optimizer will take into account both per-hour and vehicle cost. Given other limitations such as time_windows, talents, task location, vehicles, and so on, the route with lesser costs is generally favored over other routes.

6. Depots

Depots are a center for completing customer orders and are an essential part of any logistic operation. They can serve orders within a certain area of a major city, fulfil orders of numerous or single inventory categories, facilitate reverse logistics scenarios, and perform many other tasks in last-mile or on-demand delivery lines. 

With four depots, Nextbillion can fulfill orders for a variety of product categories and geographical areas. With these depots, they aim to complete eight orders, six deliveries, and two pickups. The Route Optimization Flexible API from NextBillion.ai can effectively address depot-related route planning issues by simulating real-world depot operating factors.