In this paper, a robust bi-level model is proposed to optimize decisions related to distribution and evacuation aid after earthquake. Usually in disastrous situation foreign countries help the affected country by sending relief commodities. In this problem, the foreign countries try to minimize their shipping costs and the affected country seeks to minimize its total costs which include inventory, operation, and transportation expenses. This situation is a game between different decision makers after a catastrophic disaster. To deal with this situation, a bi-level model is proposed in which the affected country is the leader and suppliers are the followers. To validate the proposed robust model, we consider Tehran probable earthquake in region 1 as a case study. Then the advantages of using bi-level modeling against considering just one player's point of view is provided. The sensitivity analysis of the experiments are presented to explore the effects of various parameters to show managerial insights that can guide DMs under a variety of conditions.

In recent years, many studies on the multi-agent scheduling problems in which agents compete for using the shared resources, have been performed. However, relatively few studies have been undertaken in the field of the multi-agent scheduling in a flowshop environment. To bridge the gap, this paper aims at addressing the two-agent scheduling problem in a two-machine flowshop. Because of the importance of delay penalties and efficient resource utilization in many manufacturing environments, the objective is to find an optimal schedule which has the minimum total tardiness for the first agent’s jobs, under the makespan limitation for the second agent. Since this problem is strongly NP-hard, several theorems and properties of the problem are proposed to apply in exact and meta-heuristic methods. Also, for some instances of the problem for which exact methods cannot achieve optimal solutions in a reasonable amount of time, a tabu search algorithm is developed to achieve near-optimal solutions. Computational results of the tabu search algorithm show that the average absolute error value is lower than 0.18 percent for instances with 20 to 60 jobs in size.

A single machine batch processing problem with release dates to minimize the total completion time (1|rj,batch|Σ Cj ) is investigated in this research. An original mixed integer linear programming (MILP) model is proposed to optimally solve the problem. Since the research problem at hand is shown to be NP-hard, several different meta-heuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) are used to solve the problem. To find the most performing heuristic optimization technique, a set of test cases ranging in size (small, medium, and large) are randomly generated and solved by the proposed meta-heuristic algorithms. An extended comparison analysis is carried out and the outperformance of a hybrid meta-heuristic technique properly combining PSO and genetic algorithm (PSO-GA) is statistically demonstrated.

Capacitated maximal covering location problems (MCLP) have considered capacity constraint of facilities but these models have been studied in only one direction. In this paper, capacitated MCLP and dynamic MCLP are integrated with each other and dynamic capacity constraint is considered for facilities. Since MCLP is NP-hard and commercial software packages are unable to solve such problems in a rational time, Genetic algorithm (GA) and bee algorithm are proposed to solve this problem. In order to achieve better performance, these algorithms are tuned by Taguchi method. Sample problems are generated randomly. Results show that GA provides better solutions than bee algorithm in a shorter amount of time.

This study aims to design a new model for selecting most fitting new product development projects in a pool of projects. To catch the best model, we assume new products will be introduced to the competitive markets. Also, we suppose the revenue yielded by completed projects can be reinvested on implementation of other projects. Other sources of financing are borrowing loans from banks and initial capital of the firm. These limited resources determine most evaluated projects to be performed. Several types of interactions among different projects are considered to make the chosen projects more like a portfolio. In addition, some numerical examples from the real world are provided to demonstrate the applicability of the proposed model. These examples show how the particular considerations in the suggested model affect the results.

Optimum design and control of a Combined Cooling, Heating and Power generation (CCHP) system, in addition to the economic benefits, could be profitable in environmental and energy consumption aspects. The aim of this study is to determine the optimal capacity of equipment and define the best control strategy of a CCHP system. Since determination of optimal system control strategy has a huge impact on improving the objective functions, the system’s performance under five different strategies (developed based on well-known Following Electrical Load (FEL) and Following Thermal Load (FTL) strategies) is evaluated. In a real case study, a CCHP system is designed for an educational complex located in Mahmoudabad, Mazandaran, Iran. The objective is to minimize capital and operational costs, energy consumption, and CO2 emissions of the system. Due to the complexities of the model, genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm are used to find the optimal values of the decision variables. The results show that using FEL strategy CO2 emissions reduces in compression to FTL strategy. Furthermore, using multiple power generation units under FTL strategy eventuates the least cost but increases CO2 emissions and energy consumption in compression to FEL strategy.

In recent years, the increased incidence of natural disasters with irreparable damage to people has led to various efforts to reduce its destructive effects and consequences. Hence, humanitarian aid logistics are aimed at preserving life and reducing the suffering of people in crises. Facility location is a strategic issue in humanitarian logistics and has a planning role before the crisis. Finding the right place for establishment of the facilities can help relieve the disaster. This research is also based on the principles of non-operational defense and the design of a multi-objective mathematical model for seeking a suitable location for the facility. In this mathematical model based on four population density indexes, user appropriateness, access to the road and enclosure of the appropriate location for the establishment of a hospital, temporary care centers, shelters and warehouses is selected. The designed model is solved using Lexicographic method and via GAMS software.

The purpose of this study is to investigate the effect of empowerment aspects on the competence level and success of the primary school principals in Pakdasht city in Iran. This research is a descriptive-survey method and in terms purpose is practical. The statistical population of this study consisted of principals of the primary schools in Pakdasht city. The total number of primary school principals in this city is 135 people (75 male schools and 60 female schools). As data gathering tool, a researcher-made questionnaire was used. In order to analyze the validity of the questionnaire in this study, the Content Validation Method was used in which the questionnaires were first examined by the experts and the necessary corrections were made. The reliability of the questionnaire was evaluated using Cronbach's alpha coefficient. Research hypotheses were tested using structural equation modeling and AMOS software. The results show that competence and effectiveness aspects affect competence and success of principals of the Pakdasht elementary schools. Autonomy affects the competence level of elementary school principals in Pakdasht city but does not affect principals' success. Meaningfulness aspect did not affect principals’ competency however it is effective on principals’ success in Pakdasht elementary schools. Trust aspect was not effective on the Pakdasht elementary schools principals’ competence and success.

Innovation is one of the key factors distinguishing organizations from competitors in today’s high-ly competitive markets. Therefore, improving innovative performance is critical for creating com-petitive advantage. On the other hand, availability of information and knowledge can be defined as one the best ways to increase the innovation ability of organizations. Many theorists as well as practitioners emphasize on knowledge management as an enabler in enhancing organizational inno-vation. Hence, This study is carried out in the Fars governor in Iran during the year of 2017 to in-vestigate the relationship between the knowledge-based leadership and knowledge management and innovation performance. This study is descriptive / survey and the data collection is a cross-sectional and data questionnaire is used to collect the required data. Data analysis and hypotheses testing have indicated a significant relationship between knowledge-based leadership and knowledge management and innovation performance in Fars governor. The results also suggest a relationship between knowledge-based leadership and the knowledge management activities with a coefficient of 0.97. In addition, There is also a positive and meaningful relationship between knowledge management and innovation performance with a coefficient of 0.73 and between knowledge-based leadership and innovation performance with a coefficient of 0.73. The results al-so led to the existence of a relationship between knowledge based leadership, knowledge manage-ment practices and innovation performance with a coefficient of 0.7081.

The purpose of this research is to design a crisis management model in the archival centers of Iran during the pre-crisis phase. The present study was conducted with a qualitative approach using the Grounded theory method. The necessary data was collected using semi-structured interviews. Data saturation was a major factor in determining the sample size. The research population included 20 crisis management specialists and managers of archives in Iran and the data analysis was performed in three stages: open, axial, and selective coding. The paradigmatic model derived from the findings of the research includes the sections of the causal conditions, strategies, intervening conditions and the underlying conditions and their outcomes. The causal conditions are located in two categories of internal crises such as biological crises and lack of proper management, and external crises such as natural disasters, fires and human-made crises. Intervener conditions and backgrounds include cat-egories such as lack of specialist staff training, lack of appropriate environmental conditions and management mechanisms, archival building and human resources issues. To prevent and mitigate the effects of the crisis in archives, some strategies are required such as modern education for resil-ience, teaching how to use documents, standardizing buildings and equipment (non-use of steel skeletons in building archives, use of concrete skeletons Armed or metal, as well as the use of walls and doors and floors of anti-fire covers) in the building of archives and the establishment of multi-layer protective systems for the protection of documents.