Multi-objective Optimization of Production Using Simplex, Goal Programming, and Pareto Front Models

Farmers are the essential actor in the productivity chain. However, they can also be the weakest ones. In Indonesia, the distribution chain is mostly a long process that impacts farmers, collectors, wholesalers, retailers, and consumers. An ideal distribution chain needs an optimization model involving good decision-making from governments in planning, production, warehouse, and transportation. Simulation-based optimization aims to provide adequate consumer stock, increase farmers' profits, and minimize production costs. The proposed framework integrated three methods of Optimization Simplex using POM QM, Optimization Goal Programming using POM QM, and Pareto Front using Phyton. This research focuses on optimization using the simplex method to fulfill the objective function with a maximum limit of more than one variable. The parameters are market demand, stock, harvest season, and price. Re-optimization using goal programming is also used to minimize the deviation for the goal function and Pareto front. An optimization model or Multi-Objective Optimization is the solution for multiple problems using linear programming. This method is the development from the previous research purposed at finding the answer to the product optimization problem by cutting the distribution transaction into four; farmers sell products to KUD (Cooperatives Village Unit), KUD holds buying and selling process between farmers, farmers, and distributors sell products to KUD, and consumers purchase the product from KUD. The research shows the optimization results of the average price are up to 8913060, and the middle market hole is up to 17741000.