develop a code that use pyswarm library to solve optimization model written in pyomo -- 2
Budget: $30 – $250 USD
I have an optimization problem of integer binary programming which already written in python and I solved it through pyomo library by using cplex solver. I need somone who can develop algorithm to solve the problem by using heuristic algorithm such as particalr swarm or use the pyswarm pyswarms.discrete.binary module to return soluation near to cplex result in short time .
Requirement List:
Problem Description: I will Provide a detailed description of the logistic healthcare optimization problem that I want to solve using GA or PSO. This should include the objectives, constraints, decision variables, and parameter
Input Data: I will provide the input data needed to solve the problem. This may include data such as demand for healthcare services, transportation costs, and location data for healthcare facilities.
Algorithm Selection: Select either GA or Particle Swarm Optimization (PSO) to solve the optimization problem. Explain the reason for choosing the selected algorithm and why it is a good fit for the problem.
Code Development: Develop code to implement the selected algorithm using the existing formulation. This code should be able to solve the problem and return similar results to those obtained using CPLEX. ( there is an example to show you the result of cplex )
Parameter and Decision Variable Settings: I will provide it in excel .Allow me for the modification of parameters and decision variables in the code to run additional experiments and increase the size of the problem set.
Pseudocode: Provide pseudocode for the algorithm to help understand the implementation of the algorithm and its optimization process.
Testing: Test the code to ensure it is running correctly and producing accurate results.
Requirement List:
Problem Description: I will Provide a detailed description of the logistic healthcare optimization problem that I want to solve using GA or PSO. This should include the objectives, constraints, decision variables, and parameter
Input Data: I will provide the input data needed to solve the problem. This may include data such as demand for healthcare services, transportation costs, and location data for healthcare facilities.
Algorithm Selection: Select either GA or Particle Swarm Optimization (PSO) to solve the optimization problem. Explain the reason for choosing the selected algorithm and why it is a good fit for the problem.
Code Development: Develop code to implement the selected algorithm using the existing formulation. This code should be able to solve the problem and return similar results to those obtained using CPLEX. ( there is an example to show you the result of cplex )
Parameter and Decision Variable Settings: I will provide it in excel .Allow me for the modification of parameters and decision variables in the code to run additional experiments and increase the size of the problem set.
Pseudocode: Provide pseudocode for the algorithm to help understand the implementation of the algorithm and its optimization process.
Testing: Test the code to ensure it is running correctly and producing accurate results.