This study contributes to the fresh food supply chain system due to the lack of carbon emissions and food waste reduction that the prior studies neglected. This study examines a fresh-food supply chain system with multiple farmers, a single processor, multi-distributor, customers, and multiple periods. This paper presents a mixed-integer linear programming to optimize total purchasing, inspection, food waste, packing, cold storage, transportation, and carbon emission costs by optimizing product inventories and deliveries. The model is also validated to provide insights into relevant industries. The results show that the total distribution cost from distributor to customers, the total purchasing cost, and total packaging cost are 38.68%; 25.87%; and 16.84%, respectively. In addition, sensitivity analyzes show that the total costs and emissions are significantly affected by the variance in temperature control, carbon punishing cost, and vehicle types. Furthermore, this research can guide the decision-makers by considering the influence of these parameters. Graphical abstract

In order to identify the optimal structure of an electricity power network under the main assumption of a price dependent demand of electrical energy, we presented an optimization model that aims at analyzing the effect of price-dependent demand on the sustainable electrical supply chain system (SESCS). The system included a power generation system, transmission and distribution substations, and many customers. The electrical energy was generated and transmitted through multiple substations to our customers, and the demand for electricity by the customers is dependent on the price of electricity. In the study, we considered the transmission and the distribution costs which depend on the capacities of power generation, transmission rates and distances between stations. We utilized the inventory theory to develop our model and proposed a procedure to derive an optimal solution for this problem. Finally, numerical examples and sensitivity analysis are provided to illustrate our study and consolidate managerial insights.