fatemeh hajisoltani

The main objective of this research is effective planning as well as greener production and distribution of mineral products in supply chain network. Through a case study in cement industry, it considers the design of the mining supply chain network including several factories with a number of production lines and multiple distribution centers. It leaves part of the transportation operation to contractor companies so as to enable the core company to better focus on its products’ quality and also create job opportunities to local people. It employs a multi-period and multi-product mixed integer linear programming model to both maximize the profit of the factory as well as minimize its carbon dioxide gas emissions which are released during cement production and transportation process. Due to the uncertainty of its cost parameters, fuzzy logic has been used for the modeling and solved via a novel fuzzy multi-choice goal programming approach. Sensitivity analysis has also been done on some key parameters. Comparing results of the model with those from the single-objective models, shows that the model has good efficiency and can be used by managers of mining industries such as cement. Although leaving part of the transportation operations to contractor companies increases the number of vehicles used by the contractor companies, its associated decrease in the number of required factory vehicles, improves both objectives of the model. This should be considered by the managers since on top of profit maximization, it can help them build an eco-friendly image. Mining industries generally generate significant amount of pollutions and companies that pay attention to different dimensions of their social responsibilities can remain stable in the competitive market.

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation in preventive health care programs is a critical factor in terms of their effectiveness and efficiency of these programs. This article presents a methodology for locating preventive health care facilities (PHCFL) in order to increase the accessibility to potential clients and thus maximize participation in preventive healthcare programs. Due to capacity constraints in preventive health care facilities and the importance of waiting time in queues, we assume that each facility acts as M/M/ /  queuing system. We present an Integer nonlinear programming (INLP) model in order to maximize the participation rate and minimize the cost of building facilities and allocating medical equipments to open facilities. Because of the importance of other objective functions, supplements have been introduced to bring about equitable access to preventive health care centers and to balance the hours of servant unemployment.The model is known as NP-Hard models, hence we propose two meta-heuristics algorithms to solve this problem with multi-objective functions. Meta-heuristics algorithms are consists of: non-dominated sorting genetic algorithm and non-dominated ranking genetic algorithm. In order to increase the speed and performance of the combinatorial optimization algorithms, new coding is used in these solution algorithms. Finally, we used Taguchi method to tune the parameters of two algorithms and test problems with different size were generated and analyzed. According to the results, non-dominated sorting genetic algorithm is better.