Multiobjective optimization in delivering pharmaceutical products with disrupted vehicle routing problem

Bouchra, Bouziyane; Dkhissi, Btissam; Cherkaoui, Mohammad

doi:10.5267/j.ijiec.2019.7.003

Cited by 7 publications

(4 citation statements)

References 30 publications

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“…Yan (2020) improved the delivery efficiency and resource utilization for a pharmaceutical enterprise by applying improved GA and saving method to design distribution scheme. Bouziyane et al (2020) studied the disrupted VRP with soft time windows. They proposed an improved multi-objective local search utilizing a combination of GA and variable neighborhood search (VNS) to improve the efficiency of pharmaceutical distribution.…”

Section: Introductionmentioning

confidence: 99%

Model and algorithm for pharmaceutical distribution routing problem considering customer priority and carbon emissions

Li,

Peng,

Deng

et al. 2024

DCE

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Pharmaceutical distribution routing problem is a key problem for pharmaceutical enterprises, since efficient schedules can enhance resource utilization and reduce operating costs. Meanwhile, it is a complicated combinatorial optimization problem. Existing research mainly focused on delivery route lengths or distribution costs minimization, while seldom considered customer priority and carbon emissions simultaneously. However, considering the customer priority and carbon emissions simultaneously will not only help to enhance customer satisfaction, but also help to reduce the carbon emissions. In this article, we consider the customer priority and carbon emission minimization simultaneously in the pharmaceutical distribution routing problem, the corresponding problem is named pharmaceutical distribution routing problem considering customer priority and carbon emissions. A corresponding mathematical model is formulated, the objectives of which are minimizing fixed cost, refrigeration cost, fuel consumption cost, carbon emission cost, and penalty cost for violating time windows. Moreover, a hybrid genetic algorithm (HGA) is proposed to solve the problem. The framework of the proposed HGA is genetic algorithm (GA), where an effective local search based on variable neighborhood search (VNS) is specially designed and incorporated to improve the intensification abilities. In the proposed HGA, crossover with adaptive probability and mutation with adaptive probability are utilized to enhance the algorithm performance. Finally, the proposed HGA is compared with four optimization algorithms, and experimental results have demonstrated the effectiveness of the HGA.

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Section: Introductionmentioning

confidence: 99%

Model and algorithm for pharmaceutical distribution routing problem considering customer priority and carbon emissions

Li,

Peng,

Deng

et al. 2024

DCE

View full text Add to dashboard Cite

show abstract

“…The method uses a hybrid algorithm-based neighbourhood search in vehicle route optimisation. The method is effective in meeting the dynamic needs of customers [10]. The AFSA is an important part of modern heuristic algorithms, mainly used in engineering optimization, economic management, machine learning and other fields.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Path Optimization Model of IOT Delivery Vehicles for E-commerce Logistics Distribution

2023

SCPE

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Logistics and distribution is a vital link to guarantee the stable supply of the e-commerce market and the healthy development of the industry. With the constant growth of the e-commerce, the efficiency and service quality of logistics and distribution have been paid more and more attention to. Therefore, the study firstly Considering distribution fixed cost, transportation penalty cost and carbon emission cost, the vehicle routing optimization model is transformed into the lowest transportation cost model, then uses an improved traditional artificial fish swarm algorithm to find the optimum way for this model, and finally verifies its performance and applicability through experiments. The performance test results show that the algorithm finds the optimal solution 3589 and 3590 in 63 and 78 iterations in the Oxford Robot Car dataset and Apollo Scape dataset, respectively; the average running time of the algorithm is 11.864s and 11.967s in the 10 operation time tests; in the operation function test, the algorithm. The algorithm was able to overcome the local optimal solution problem. The applicability simulation shows that this algorithm stabilizes after 53 iterations, the minimum cost of the optimal solution of the model is $41,224, and the total distance of distribution is 9035 km. The research algorithm is fast in finding the optimal value, which is close to it, indicating that the algorithm is highly efficient and reliable, and can greatly optimize the path of e-commerce logistics delivery vehicles, and give a theoretical foundation for the optimization of logistics delivery paths in other industries.

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“…Their objectives were to decide the optimal procurement, production, and shipment strategies that minimize the combined system costs. Additional works that investigated diverse features of multi-shipment policies in different aspects of supply chain systems can be found elsewhere [25][26][27][28][29]. Since few studies focused on exploring the combined effects of outsourcing, in-house quality assurance matters, and multiple deliveries on the optimal fabrication-delivery policy, this paper aims to fill the gap.…”

Section: Introductionmentioning

confidence: 99%

Incorporating an outsourcing strategy and in-house quality assurance into the production-shipment decision making

Chiu¹,

Li²,

Chiu³

et al. 2022

J Appl Eng Science

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To stay competitive in turbulent business environments, manufacturing firms’ managers today constantly seek ways to reduce order response time, smooth production schedules, ensure the quality of their products, and lower overall making and shipping costs. This study incorporates an outsourcing strategy and in-house quality assurance into a production-shipment problem to address the aforementioned operational goals. The objectives are to simultaneously find the optimal fabrication batch size and frequency of delivery that minimize the system’s relevant costs and reveal in-depth information regarding the impact of diverse system parameters on the optimal policy and system cost. This study develops a model and uses the optimization method to resolve the problem. The research results facilitate managerial decisions in such a real-life situation.

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Multiobjective optimization in delivering pharmaceutical products with disrupted vehicle routing problem

Cited by 7 publications

References 30 publications

Model and algorithm for pharmaceutical distribution routing problem considering customer priority and carbon emissions

Model and algorithm for pharmaceutical distribution routing problem considering customer priority and carbon emissions

A Dynamic Path Optimization Model of IOT Delivery Vehicles for E-commerce Logistics Distribution

Incorporating an outsourcing strategy and in-house quality assurance into the production-shipment decision making

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