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

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.

Customized Approach to Greenhouse Gas Emissions Calculations in Railway Freight Transport

The topic of global warming is and will continue to be a crucial topic of this millennium. Freight transport, as a producer of greenhouse gas (hereinafter GHG) emissions, makes a significant contribution to the greenhouse effect. Large supply chains and large volumes of freight transport, which imply the production of significant volumes of GHG emissions, characterize the automotive industry (hereinafter AI). Thanks to these premises, it is necessary to seek and develop tools for reducing the volume of GHG emissions produced from the logistic activities of the AI, while maintaining the required level of logistic services. The assumptions for the calculation of GHG emissions from railway freight transport (hereinafter RFT) in the AI were identified through the use of semi-structured interviewing. Available railway freight GHG emission calculators were identified and analyzed from the perspective of suitability for the AI using a comparative content analysis. The main result of this manuscript is the proposal of a fully customized approach to GHG emission calculations in RFT for the AI. This approach was proposed, applied, and verified in the form of an interpretative case study. The use of this approach can be expected in support of logistic planning and decision making.

A multi-objective optimization model for logistic planning in the crisis response phase

PurposeProper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.Design/methodology/approachThe main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. 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 transportation activities as the second objective function while maintaining the optimality of the first objective function.FindingsThe performances of the proposed model were analyzed in different cases and its robust approach for different problems was 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 implicationsThe proposed methodology can be applied to find the best response plan for all crises.Originality/valueIn this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.

Framework for Greenhouse Gas Emissions Calculations in the Context of Road Freight Transport for the Automotive Industry

The topic of greenhouse gas emissions calculations in the context of freight transport is very current. This topic is very interesting for many stakeholders, such as companies, suppliers, employees, customers, residents, etc. The automotive industry is a major producer of greenhouse gas emissions from logistic processes. Due to this fact, it is necessary to search for and create frameworks for the calculation of greenhouse gas emissions in this sector. The requirements for the calculation of greenhouse gas emissions from road freight transport in the automotive industry were identified using semi-structured interviews. Available emission freight calculators were analyzed using the content and comparative analysis. The proposed frameworks for greenhouse gas emissions calculations in the context of road freight transport of material and finished manufactured passenger cars for the automotive industry were applied in the form of an interpretative case study. The main result of the article is the proposal of the frameworks for greenhouse gas (carbon and sulfur dioxide) emissions calculations in the context of road freight transport of the material and finished manufactured passenger cars for the automotive industry. The proposed frameworks were applied and verified. The use of the proposed frameworks can be expected in logistic planning and decision-making.

Road Centerline Data Accumulation for Rescue Workers Whose Expertise Is Not GIS

ABSTRACT Objectives: The objective of this study is to provide road centerline data for professionals of disaster medicine areas who are often beginners in GIS use. Methods: Newly developed vector tile format data were converted into shapefile format data, then were organized as second level medical districts to which medical professionals are accustomed. Results: Road centerline data in Japan is being prepared to release from Association for Promotion of Infrastructure Geospatial Information Distribution free of charge. Conclusion: Professionals of disaster medicine areas increased their accessibility of GIS. Logistic planning for evacuation activities and dispatching of rescue teams were improved.