Sina Nayeri, Ebrahim Asadi-Gangraj, Saeed Emami,
Volume 29, Issue 1 (3-2018)
Abstract
Natural disasters, such as earthquakes, tsunamis, and hurricanes cause enormous harm during each year. To reduce casualties and economic losses in the response phase, rescue units must be allocated and scheduled efficiently, such that it is a key issues in emergency response. In this paper, a multi-objective mix integer nonlinear programming model (MOMINLP) is proposed to minimize sum of weighted completion times of relief operations as first objective function and makespan as second objective with considering time-window for incidents. The rescue units also have different capability and each incident just can be allocated to a rescue unit that has the ability to do it. By assuming the incidents and rescue units as jobs and machine, respectively, the research problem can be formulated as a parallel-machine scheduling problem with unrelated machines. Multi-Choice Goal programming (MCGP) is applied to solve research problem as single objective problem. The experimental results shows the superiority of the proposed approach to allocate and schedule the rescue units in the natural disasters.
Fatemeh Hajisoltani, Mehdi Seifbarghy, Davar Pishva,
Volume 34, Issue 1 (3-2023)
Abstract
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.
