The environmental changes caused by industrial activities have spurred a significant interest in designing supply chain networks by considering environmental issues such as CO2 emission. The pivotal role of taking uncertainty and risk into account in closed-loop supply chain networks has induced numerous researchers and practitioners to develop appropriate decision making tools to cope with these issues in such networks. To design a supply chain regarding environmental impacts under uncertainty of the input data and to cope with the operational risks, this paper proposes a multi objective possibilistic optimization model. The proposed model minimizes traditional costs such as cost of products shipment, purchasing machines and so on, as well as minimizing the environmental impact, and as a results strikes a balance between the two objective functions. Furthermore, in order to solve the proposed multi objective fuzzy mathematical programming model, an interactive fuzzy solution approach is applied. Numerical experiments are used to prove the applicability and feasibility of the developed possibilistic programming model and the usefulness of the applied hybrid solution approach.

The purpose of this study is to determine the role of the logistics industry in the sustainable economic development in the context of Southeast Asian countries. This study is quantitative in nature where the data are gathered from the secondary sources. The analysis is carried out with the help of correlation, feasible generalized least square model (FGLS). The outcome of this study confirms the significant impact of LPI on GDP growth, CO2 emission and current health expenditure. Similarly, the significant impact of FDI is found on all the dependent variables of this study. In contrast, the variable of TOP is found to have a significant impact on both CO2 emission and current health expenditure, whereas it makes an insignificant impact on GDP growth. The absence of qualitative data is one of the major limitations of this study. Apart from that, the limited scope of this research on Southeast Asian countries is another limitation.

Recently, researchers have focused on how to minimize the negative effects of industrial activities on environment. Consequently, they work on mathematical models, which minimize the environmental issues as well as optimizing the costs. In the field of supply chain network design, most managers consider economic and environmental issues, simultaneously. This paper introduces a bi-objective supply chain network design, which uses fuzzy programming to obtain the capability of resisting uncertain conditions. The design considers production, recovery, and distribution centers. The advantage of using this model includes the optimal facilities, locating them and assigning the optimal facilities to them. It also chooses the type and the number of technologies, which must be bought. The fuzzy programming converts the multi objective model to an auxiliary crisp model by Jimenez approach and solves it with ?-constraint. For solving large size problems, the Multi Objective Differential Evolutionary algorithm (MODE) is applied.