A fuzzy decision support system for evaluating Lean-Green and company-specific production system.

Lean production is regarded as systematic solution for identifying and eliminating waste through continuous improvement of manufacturing processes to meet customers' requirements. Due to rising environmental concerns and the significant environmental impact of companies operations, issues such as environmental management and green production are on board agendas. In essence, green production seeks to reduce the environmental impacts of business processes.

Evaluation of the effective factors of unloading and loading goods in ports and the impact on the environment using the MCDM method.

Today, the impact of transportation on sustainable development is undeniable. Maritime transport, as one of the important pillars of this industry and due to its advantages such as low cost and large volume of freight, plays a key role in the development of foreign trade. This study uses TOPSIS and DEMATLE methods to evaluate the factors affecting the unloading and loading of goods on the port's environment.

Modeling a periodic electric vehicle-routing problem considering delivery due date and mixed charging rates using metaheuristic method.

The coupling of ever-increasing consumption of fossil fuels around the globe with the decrease in the availability of fossil fuel supplies has led to an increased cost of energy commodities, which together with ever-expanding requirements for reducing the level of environmental pollutions has resulted in an ever-increasing deal of attention to alternative transportation schemes such as electric vehicles (EVs). Since decades ago, national governments and environmental activists have initiated various efforts towards reducing atmospheric pollutions. A part of such effort has been focused on reducing the use of internal combustion vehicles and rather replacing them with EVs.

Evaluation of green lean production in textile industry: a hybrid fuzzy decision-making framework.

Textile industry is an old and effective industry in Iran. However, due to its age and high energy consumption, this industry has low profitability and entrepreneurship. One of the most important problems of the weaving industry is the issue of waste regarding manpower, materials, machinery, and especially energy consumption.

Green reverse supply chain network design considering location-routing-inventory decisions with simultaneous pickup and delivery.

In this work, a bi-objective mixed-integer linear programming model is formulated for the first time to design a green supply chain while considering both forward and reverse flows, location-inventory-routing problem with simultaneous pickup and delivery, scheduling of vehicles, and time window. This model is presented to manage the production and distribution of perishable products and aims to minimize total costs and lost demands simultaneously. To solve the proposed bi-objective model under uncertainty, an approach based on fuzzy theory is developed.

An artificial neural network based mathematical model for a stochastic health care facility location problem.

This research is conducted to investigate the problem of locating the trauma centers and helicopters' station in order to optimize the trauma care system. The stochastic characteristics of the system, such as stochastic transferring time of the patients, stochastic demand and stochastic servicing time of the patients in trauma centers are taken into account. The problem is first modeled as a stochastic mixed-integer linear mathematical model.