A novel optimisation model in the collaborative supply chain with production time capacity consideration

Abstract

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.

Energy‐efficient and sustainable supply chain in the manufacturing industry

“…LaRoche‐Boisvert et al 26 investigated the integration of mine‐to‐port transportation into production planning and proposed a long‐term stochastic integer programming model to optimize multiple objective functions, including production scheduling costs at the mines, stockpile reclamation costs, the equipment fixed cost, mining and mine‐to‐port transportation costs, and the risks related to meeting product demand at the port. Beheshtinia et al 27 studied integrated production and scheduling problem in a supply chain considering distributed manufacturing system. They developed a new GA named GA‐TOPKOR to minimize the total orders' delivery time, transportation and production costs, and pollution level, and maximize the quality of completed orders.…”

“…After presenting two mathematical models for the problem, they proposed a hybrid GA to solve the problem. Purnomo et al 25 discussed a collaborative supply chain in the furniture industry and tried to minimize material, processing, transportation, and holding costs. They developed a mathematical model to formulate the considered objective functions and proposed a GA to solve the problem.…”

Supply Chain Optimization Considering Sustainability Aspects

“…Furthermore, a hybrid genetic algorithm is proposed to solve the problem in large-scale problems. Purnomo, Anugerah [24] discussed a collaborative supply chain in the furniture industry and tried to minimize material, processing, transportation, and holding costs. They developed a mathematical model and proposed a genetic algorithm to solve the problem.…”

“…The current research also differs from the previous studies by addressing the SCCP while integrating transportation and production scheduling and considering multiple objectives, namely minimizing the total orders' delivery time, transportation and production costs, pollution levels, and maximizing the quality of completed orders. Single machine Heuristic [6] Single machine GA [7] Flexible flow shop [8] Single machine [9] Single machine GA [10] Single machine [11] Parallel machines Heuristic [12] Single machine Heuristic [13] Single machine GA [14] Single machine GA [15] Single machine GA [16] Single machine MLCA [17] Single machine GA [18] Single machine Heuristic Single machine GA [20] Single machine Heuristic [21] Assembly Flowshop Heuristic and IGA [22] Single machine [23] Single machine GA [24] Single machine GA [25] Assembly Flowshop IGA [26] Single machine [27] Single machine GA [28] Single machine PSO…”