Logistic planning for pharmaceutical supply chain using multi-objective optimization model

• Published in: International journal of pharmaceutical and healthcare marketing 2022-02, Vol.16 (1), p.75-100
• Main Authors: Ershadi, Mohammad Mahdi, Ershadi, Mohamad Sajad
• Format: Article
• Language: English
• Subjects: Case studies; Costs; Genetic algorithms; Heuristic methods; Human error; Integer programming; Inventory; Literature reviews; Logistics; Mathematical programming; Multiple objective analysis; Objective function; Optimization; Optimization models; Particle swarm optimization; Pharmaceuticals; Planning; Sensitivity analysis; Sorting algorithms; Suppliers; Supply chains
• ISSN: 1750-6123; 1750-6131
• DOI: 10.1108/IJPHM-01-2021-0004

Purpose Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests. Design/methodology/approach The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim. Findings The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors. Practical implications The proposed methodology can be applied to find the best logistic plan in real situations. Originality/value In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.