Optimization of the conventional bike-sharing system

There is the problem of fleet unbalance, particularly during peak hours in conventional systems. This generally leads to service unavailability and to counter this issue we employ a rebalancing operation. Therefore, a simulation model should be developed to assess the profit and costs of conventional bike-sharing. This simulation model should integrate the key elements of bike-sharing service, mainly the management decisions.

1. Identifying the suitable strategies (For example, heuristic algorithms) that can be implemented in our simulation testbed, considering our system design and the demand data.
2. Implementation and testing of any two heuristic algorithms like Mixed Integer algorithm, branch and bound algorithm, management strategies in our developed simulation model in Anylogic.
3. Execution of a comparative study by evaluating different KPIs from the simulation(mainly rebalancing costs, service rate, number of bikes needed for a given service rate, and waiting time)
4. A small simulation model with 20 stations and a single depot needs to be simulated and optimized using any two above-mentioned heuristic algorithms.