Optimization of a logistics network considering allocation of facilities and taxation aspects

Abstract

This article analyzes the impacts of operational and tax changes in a logistics network, considering the location of facilities and the following taxes: the Brazilian State Excise Tax on Circulation of Goods and Services, the Import Duty, the Brazilian State Excise Tax in Tax Substitution, the Social Integration Program, the Contribution for the Financing of Social Security and the Brazilian Federal Excise Tax on Industrialized Products. The influence of incorporations and outsourcing of distribution services in solving global localization issues concerning various links in a chain suplly has also been considered. The problem was modeled and solved by the GAMS modeling language using Solver CPLEX. The proposed Mixed Integer Linear Programming model minimizes operating costs taking into account tax benefits and the best use of the credits related to the Tax on Circulation of Goods and Services of a multiproduct network. A real application involving a company in the animal feed production sector was developed. The results showed that the model allowed to evaluate conveniently how the choice of the facilities and the characteristics of the product flows impacted the overall costs of the system. The results also evidenced the need to make decisions based on the existing tax structure, since the scenarios without tax optimization generated substantial losses to the companies. This information added quality to the manager of the company studied.

Determining regions for installing flex-biomass sugar-ethanol plants: a multicriteria approach for location

“…The technology is not yet extensively employed in the Brazilian industry (Castiñeiras & Pradelle, 2020), but a venture such as a flex plant must remain operating in the same location for several years. Furlanetto et al (2020) evidenced the complexity of the Brazilian taxation system. The authors concluded that this factor is essential for generating solid and resilient operating strategies, demanding a good assessment of taxes to avoid tax losses.…”

“…Attractive and repulsive factors of the region (Schettini & Azzoni, 2013;Sharma et al, 2017;Souza et al, 2020), elements such as time and space (Barquette, 2002), cost and quality (Rosa et al, 2015), accessibility to transport (Durmuş & Turk, 2014), land rent (Verhetsel et al, 2015) and the triple bottom line (Kheybari et al, 2019) can also be considered in these analyses. In this sense, the Analytic Hierarchy Process (AHP) proposed by Saaty (1990) can support to address spatial components in a Geographic Information System (GIS), allowing the definition of appropriate geographic locations (Alves & Alves, 2015;Al Garni & Awasthi, 2017).This combination (AHP+GIS) enables the manipulation of spatially distributed large data volumes (Furlanetto et al, 2020), simplifying the decision-making process (Gonçalves et al, 2020) and generating a tool to support planning (Rosa et al, 2015;Valladares et al, 2012).…”

Modelo Matemático De Integración De Producción E Inventarios en Una Red Logística Plantas, Distribuidores Y Detallistas

“…Con el avance de la tecnología de la información, la manufactura global está dentro del alcance de muchas organizaciones pequeñas que entraran a engrosar la alta competencia de mercado [10]. En el ambiente de la manufactura global, los costos logísticos dominan los gastos de las empresas manufactureras [11]. Por lo tanto, las decisiones logísticas involucran la obtención de la materia prima, producción y distribución y estas decisiones no se deben hacer por separado sino integrarlas con el fin de obtener beneficios.…”