In the current study, a green closed-loop supply chain network design for perishable products is investigated under uncertain conditions. The demands, rate of return and the quality of returned products stand as an uncertain parameter. The considered chain, based on the study of a dairy company, is a multi-period and multi-product that comprises suppliers, manufacturers, warehouses, retailers and collection centers. A mixed-integer linear programming (MILP) model is projected to minimize the cost and environmental pollutant, simultaneously. Besides, an innovative MILP robust model is developed for the problem under uncertainty. Due to the NP-hard nature of the problem, the research has developed an efficient heuristic, named YAG, to solve large-sized problems. Computational experiments conducted indicating that the YAG method has an average gap of less than 1.65 percent from the optimal solution within a reasonable time. Also, the YAG method finds the optimal solution in more than 34 percent of instances. The performance of the robust approach and the heuristic method is examined in a real case study and a diverse range of problems. The results revealed that the robust model compared to the deterministic model has better quality and seem quite more reliable. The effect of the product’s lifetime, bi-objective modeling and environmental pollutant are considered throughout the study. The results indicate that the effects of products’ lifetime and level of uncertainty vary for cost and environmental pollution objectives.
This study attempts to discover the nexus between crude oil price fluctuation after heavy oil upgrading and stock returns of petroleum companies in the U.S. Stock Exchange for the years 2008 to 2018. One of the methods of upgrading heavy crude oil is to extract asphaltene from crude oil. Considering the Asphaltene Removal (AR) as a factor in the nexus between oil price and the stock market is an innovation in the literature of energy finance. Asphaltenes cause many problems in the petroleum industry, which increases the cost of oil production and reduces the financial efficiency of oil companies. The AR is certainly one of the significant matters of the oil industry and can affect the price of oil. Therefore, changes in the price of oil can influence the price of oil company stocks. Hence, changes in stock prices will certainly affect the stock returns of oil companies. In an effort to solve this puzzle, the four financial models were employed to explore the nexus between oil price fluctuations and stock returns. The analysis of the results demonstrated that the oil price fluctuations caused by the removal of asphaltenes influence the stock returns of petroleum companies. Eventually, the theoretical hypothesis was confirmed by considering the USA as a case study. The outcomes of this investigation are a theoretical progression in areas related to the petroleum industry and the stock market that could lead to the adoption of new investment policies in the petroleum industry including investing in new procedures to manage and decrease the costs and time of the AR process, which would result in the advancement of petroleum companies. In fact, we have introduced a modern investment strategy in the oil industry aimed at reducing oil production costs, improving financial statements and increasing the stock returns of petroleum companies. Eventually, we will present new investment policies in the oil industry that can lead to economic growth and development of financial markets especially stock market, derivatives market, futures exchange, commodities exchange, as well as bond market.