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This paper presents a group decision-making model using a distance aggregator based on Ordered Weighted Distance (OWD) which offers a solution that can reduce disagreement between decision makers (DMs). This paper discusses decision rules and sets out measures to evaluate compensatory effects that have a bearing on DMs’ opinions. The model uses formulations of distances to reveal the differences in opinion among DMs and discusses the meanings of distance and the information presented by each DM. Finally, a case study of a logistics problem is used to illustrate how the model is applied.

The Amazon region has the largest hydrographic basin in the world and a favorable geographical location as a strategic export point but does not satisfactorily exploit its potential for transport and cargo flow, mainly as a differential factor of logistic competitiveness. For the waterway mode, cargo transportation is predominantly carried out by pushed convoys. The objective of this research is to evaluate and select, the best river train for the outflow of iron ore on the Marabá – Vila do Conde stretch, through a multiple criteria decision-making approach. To meet the objectives, a methodological framework is proposed using a hybrid AHP-DEMATEL method, based on a statistical analysis and to guarantee the reliability of the results for the proposed alternatives and not only considering the preference function, the ELECTRE method was used and also a parametric comparison of the AHP results. The main goals of this work were achieved and it was possible to infer that the combination of these methods has, in addition to the evident efficacy, a high reliability in the water transport area, being able to be used with accuracy of diverse forms in the academic area, as well as in industrial applications. Therefore, it can be affirmed that the best-pushed convoy configuration for the iron ore runoff in the Marabá – Vila do Conde stretch is composed by six barges in the arrangement of two columns and three rows with the measurements, by barge, with length of 60.96m; beam of 13.75m; and a 5m molded depth.

The increase in e-commerce and omnichannel commerce is having a significant impact on the supply chain sector and its warehouses. Fluctuations in demand and priorities, the requirement for value-added service, government regulations and other factors put pressure on the operational decision makers on the warehouse floor and the systems that support them. The increasing complexity of daily warehouse operations means that decision support systems will need to become more sophisticated and intelligent to assist decision makers in real-time. The aim of this literature review is to investigate how decision support in warehousing and distribution operations is examined in the research literature. The objective of this review is to understand how this decision support research can assist operational decision makers to manage and complete the daily volume of work through the warehouse. Fifty-one articles were obtained by the literature search. Articles were categorized by type of warehouse, decision support target, operational task and problem type, research article methodology, architecture and technology. Decision support is examined in almost all areas of warehousing operations with the use of a variety of methods and technologies within the research literature. Most “daily warehouse operational” decision support deals with expertise transfer and reacting to real-time events. This paper highlights the lack of research into human–machine collaboration in adaptive decision support systems to assist warehouse operational decision makers.

In recent years, the development of electronic commerce in our country to speed up the pace. The role of logistics has been highlighted, more and more electronic commerce enterprise are beginning to realize the importance of logistics in the success or failure of the enterprise. In this paper, the author take Jingdong Mall for example, performing a SWOT analysis of their current situation of self-built logistics system, find out the problems existing in the current Jingdong Mall logistics distribution and give appropriate recommendations.