فهرست مطالب s. ebrahimnejad

The increasing severity and frequency of disasters have posed major challenges for people. Amongst, the risks of fatalities and injuries of people with disabilities (PWDs) have significantly increased. The Sendai Framework for Disaster Risk Reduction (SFDRR) initiated a movement to create a "disability-accessible and inclusive environment" which highlighted the problems PWDs faced during disasters. One of the most important issues is providing evacuation and accommodation according to the special needs of PWDs. In this study, a MILP model is proposed to pick up PWDs from different locations and transfer them to shelters. Throughout this research, diverse disabilities, heterogonous vehicles, compatibility types of disabilities and vehicles, multi-depot and adept and amateur operators were considered to help evacuate PWDs. Additionally, 27 problems are solved to examine the efficacy of (μ+1) EA algorithm in large scale problems. Subsequently, a real case study with 500 nodes including pick up, shelters, and depot nodes are analyzed. The computational results illustrate that by adding small-sized (car) and medium-sized (Van) vehicles to the current fleet, the time for tours traveled significantly reduces. Finally, a sensitivity analysis has been conducted to prepare some managerial implications for crisis managers during the occurrence of disasters to help PWDs during evacuation.

This paper presents a robust location-allocation planning problem for emergency relief in a disaster situation, which is formulated as a robust optimization model. It is a multi-objective, multi-commodity, multi-vehicle and multi-level logistics model considering injury variety through service prioritizing for more injuries and considering unmet demand of particular item type in various damaged areas, public donation of different relief goods, using capacitated medical centers and emergency centers regarding damage type and capacitated relief distribution centers and disaster management centers. This a non-linear mixed-integer programming model that simultaneously optimizes three objectives; i.e., maximizing service fairness to damaged areas, maximizing fair commodity disaster management, and minimizing the total logistics cost. To solve such a hard problem, an NSGA-II is developed and the Taguchi method is applied to adjust its parameters. The ε-constraint method is used for the evaluation of the proposed algorithm performance. Three comparison metrics, including diversification, spacing and mean ideal distance, are used. The results verify the algorithm’s effectiveness in a reasonable computational time. Eventually, to examine the applicability of the presented model and the proposed algorithm, a case study is analyzed in the area located in the north of Iran, known with historical earthquake records and aggregated active faults.

In this paper, we propose an integer programming model for Capacitated Multi-Allocation Median Hub Location Problem, which is applied in a both cooperative and competitive environment among airlines. We divide the hubs into six independent categories by comparing the parameters of the ticket price, travel time, and the service quality of hub airports are controlled by follower and leader airlines. In this paper, the degree of importance of time and cost parameters determine by a multivariate Lagrange interpolation method, which can play an important role in allocating travelers to follower airline hubs. Then, based on the seasonal demand of travelers, we consider travel demand as uncertain parameters. To determine the deterministic equivalent forms of this category of hub location models, robust optimization method and chance-constrained programming model are used. Finally, the proposed model test in a case study. Based on the results, a coalition of follower airlines can absorb nearly 2% of travelers of leader airline due to lower travel cost and travel time compared to that of leader airline.

This paper aimed to design a sustainable agile retail supply chain using multi-objective optimization methods. To this end, a mathematical model was presented for the sustainable agile supply chain with five objectives, including "minimizing costs", "minimizing unanswered demand", "maximizing the quality of goods purchased from suppliers," "maximizing social responsibility or social benefits", and "minimizing environmental impacts". The NSGA-II, PESA and SPEA-II algorithms were used to solve the proposed model, which were run in MATLAB software. After collecting data from the SAIPA Company’s supply chain, the model was solved using the three algorithms. The results indicate that the SPEA-II algorithm produces more high quality responses, compared to the other two algorithms. Furthermore, the SPEA-II algorithm was found to be among the Pareto Front responses. A decrease of environmental impacts had no effect on the problem responses due to the lack of a specific structure in the current system.

Leaf (brown) rust, caused in wheat by the fungus Puccinia triticina is an important disease in north, west and south of Iran. Leaf rust is an endemic disease in Iran, which apperas in many parts of the country annually. Use of resistant cultivar is the best way to control this disease. To find resistant sources to the pathogen and use in the breeding program, it is necessary to determine virulence factors of the pathogen. In the present study, 12 locations were allocated in different parts of Iran to study virulence factors of the pathogen in trap nurseries with 37 leaf rust near isogeneic lines and a susceptible cultivar Bolani. Each line was sown in two rows of 1 meter length. The nurseries were maintained under natural infection of the pathogen. Reaction of each line was recorded at the time when infection on the susceptible control was at the maximum level, and presence of virulence for different resistance genes was determind. Results indicated presence of virulence for genes Lr1, Lr2b, Lr2c, Lr3, Lr3ka, Lr3bg, Lr10, Lr11, Lr12, Lr13, Lr14a, Lr14b, Lr15, Lr16, Lr17, Lr20, Lr21, Lr22a, Lr22b, Lr23, Lr24, Lr26, Lr30, Lr32, Lr33 and Lrb. No virulence was detected for Lr9, Lr18, Lr19, Lr25, Lr28, Lr29, Lr34, Lr35, Lr36 and Lr37 genes. Use of these genes with combination of adult plant resistance genes is expectd to be a useful method to control of leaf rust disease.