A novel optimisation model in the collaborative supply chain with production time capacity consideration
Résumé
Purpose-This study aims to propose an optimal procurement model of the collaborative supply chain in the furniture industry. The final output is the total cost minimisation to produce a furniture product that covers material cost, processing cost, transportation cost and holding cost. Therefore, if companies can give the best value to customers at a low cost, then competitive advantages can be achieved. Design/methodology/approach-A genetic algorithm (GA) as a metaheuristic approach was used to solve problems in this research. The optimisation was initiated by developing a mathematical model to formulate the objective function. Findings-Based on the case study, the proposed GA model was able to reduce the total cost of production. The cost was reduced by 73.09% compared to the existing system. Besides, the production time of the proposed model is within the capacity of both companies; hence, no penalty cost is imposed. Practical implications-The proposed GA model has been implemented and tested to minimise production costs in the Indonesian furniture industry. Originality/value-To the best of author knowledge, there is no research has proposed an optimisation model that incorporates production cost, transportation cost and production time capacity together in the collaborative supply chain. This research is the first to collaborate these factors using GA in the furniture industry.