فهرست مطالب ali mohtashami

AbstractThe purpose of this research is to identify the competencies of the members of corporate governance committees in public companies, rank the committees and create an optimal combination of competencies in them in order to implement corporate governance.The statistical population, the members of the mentioned committees and the research method are mixed. In the qualitative part, while studying the background and theoretical foundations, with judgmental sampling, twelve members of the corporate governance committees of state-owned companies and university professors were selected and interviewed, and using thematic analysis method, competencies in three dimensions, eleven components and 55 Indexes were identified.In the quantitative part, with judgmental sampling, fifteen members of the board of directors of state-owned companies implementing corporate governance were selected to complete the pairwise comparison questionnaire, and multi-criteria decision-making methods were used for analysis. The findings showed that risk, audit, service compensation, appointments and strategic committees are ranked as the most effective committees with importance coefficients of 0.976, 0.910, 0.904, 0.872 and 0.846 respectively. The most important components of competence are governance knowledge, management skills and governance skills with weights of 0.125, 0.110 and 0.099. In the end, the optimal combination of competencies in each committee was presented for the optimal implementation of corporate governance.

Steel Supply Chain (SSC) is a interpretative segment in Steel's value-creation process for ensuring on-time delivery of the right quality of raw materials, Work In Process (WIP), other goods and services to manufacturing sites, and finished products to the ultimate consumers. Graph theory provides a real-time, end-to-end view of the Steel supply chain, from suppliers to customers. By representing the supply chain as a network of interconnected nodes, graph theory provides a visual representation of the relationships between nodes including: suppliers, manufacturers, distributors, and customers. The main purpose of this study is to focus on Iran’s Steel Supply Chain (ISSC) based on complex adaptive network analysis and graph theory. Data collection performed by steel industry monitoring reports produced by relevant organizations. By mapping the Iranian SSC to the network in the Gephi environment (0.9.2), the graph theory applied to analyze node-level and network-level indices. This hypothesis tested that the corresponding network of the target SSC contained a Complex Adaptive System (CAS) which is an inception to combining social science insights to develop systems-level models and insights that allow for phase transitions and emergent behavior.

Nowadays, product recovery and waste recycling are receiving more attention in order to reduce environmental pollution and production costs in the form of a closed-loop and sustainable supply chain. Also, designing a supply chain by considering resilience approaches can protect buyers against disruptions such as natural, human or technological disasters. On the other hand, efficient and effective financial supply chain management (FSCM) way is known as one of the main structures in line with the continuity and stability of the chain's performance, and budget restrictions are of great importance considering the issue of scarcity of resources in the economy. This study has presented a multi-objective mixed integer linear programming (MOMILP) model of a single-period, multi-product and multi-level closed-loop supply chain, taking into account the dimensions of sustainability and resilience, emphasizing the balance between the initial budget and the cost of establishing facilities under uncertainty. subsequently, to eliminate the uncertainty of the demand parameters and costs, its robust counterpart was presented based on Pishvaee’s robust possibilistic programming (RPP) model. The augmented Epsilon Constraint method (AEC) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were used to solve and evaluate it.

In this paper, we have proposed a model based on Mixed Integer Non-Linear Programming for the blood supply chain under conditions of uncertainty in supply and demand, from the stage of receiving blood from volunteers to the moment of distribution in demand centers. The challenges addressed in this optimization model are the reduction of blood supply chain costs along with minimizing the shortage and expiration rate of blood products. The Markov chain has been used to address the uncertainty of donor blood supply. To estimate the needs of medical centers, the received demand is considered fuzzy. Then, the proposed model is solved in small dimensions by GAMS software and in large dimensions by Bat and Whale meta-heuristic algorithms, and the results are presented. In addition, a case study is presented to show the applicability of the proposed model. The results show a reduction in the level of costs as well as a reduction in the shortage and expiration of blood products in the supply chain.

Nowadays, the lack of natural resources and reserves of raw materials, besides the increased production costs and the problems with burying and destroying industrial waste, have attracted attention to product recovery and waste recycling in the framework of a closed-loop and sustainable supply chain, also able to create a competitive advantage. On the other hand, researches indicate that taking resilience approaches into account in supply chain design may protect buyers against disruptions such as natural, human, or technological disasters. The present paper presents a multi-objective mathematical model of a single-period, multi-product, and multi-level closed-loop supply chain, considering the dimensions of resilience and sustainability under conditions of uncertainty. Hence, a deterministic mixed integer linear programming model is initially presented; subsequently, to eliminate the uncertainty of the demand parameters and costs, its stochastic counterpart was presented based on Pishvaee's robust possibilistic programming (RPP) model. In order to solve the model, the Augmented Epsilon Constraint method was employed in the GAMS software environment. Ultimately, the model was solved and evaluated by a numerical example.

Supply chain optimization involves the integration of supply chain activities and related information flows by improving the state of chain relationships to achieve a secure and sustainable competitive advantage. In this realization, the issue of supply chain optimization has been chosen because to provide goods and services in the economy, we need a mechanism and system to maximize economic efficiency and productivity and provide return goods and services at lower and easier costs and the circular economy to be realized, the main discussion of which is related to the recycling of returned goods and goods that need to be repaired so that they can be reused. This research also emphasizes the use of healthy parts and components in the reproduction of products and this issue is considered for all goods in each part of the supply chain that cannot be used and must be transferred to the reproduction. The results of the implementation of the model presented in the genetic algorithm show that this algorithm was able to reach an almost optimal answer at the right time. This algorithm requires more computational time than LINGO optimization software to solve problems that have very small dimensions but this algorithm needs much less time to solve problems due to the increase in problem dimensions than LINGO optimization software. Therefor in these examples we observed that this algorithm can reach an acceptable answer in a much shorter interval than LINGO optimization software for large scale problems.

The generational diversity in the human force that today's organizations are facing is one of the factors of the spread of conflict in organizations. The purpose of this study is to design a model for intergenerational conflict management in Iran's government organizations.

Thematic analysis method has been used to conduct this research. The statistical population of this research was formed by academic and organizational experts. In order to collect data, a semi-structured interview was used.

The research resulted in 119 basic themes, 35 organizing themes, as well as 12 comprehensive themes (i.e., civility gap in events of meaningfulness and perceptualization, the gap in the regularization of communication general rules, self-determination framework of job value-driven, environmental-organizational divergences in generational culturalization, authenticity semantic collapse in intergenerational interactions, organizational withdrawal in intergenerational dissimilarity management, intergenerational conflicts in job ideologies, intergenerational uncertainty in job accomplishment quality, task and relational conflict bilinear orientations, selective criteria in choosing conflict management style, functionalist conflict management strategies, and interpretive conflict management strategies).

Based on the findings, it can be claimed that in order to better understand intergenerational conflicts, it is essential to find the root of the disputed areas in the structure of perceptions of generational differences, and in formulating the types of strategies, it is necessary to consider both areas of discord and conflict in the reactional way.

One of the most important issues in gas distribution companies in the country is the multi-level agility of processes in their supply chains. Therefore, the main purpose of this study was to investigate various factors in process agility using the systems dynamics approach. The statistical population of this research comprised of all managers of seven provincial gas supply companies. In this research, the Delphi method was used to identify the variables affecting process agility, statistical tests were used to analyze the correlation between data, the Dimtel method was used to classify the causal and effectual variables, and dynamic system analysis was used for dynamic model analysis and simulation. The validity of the model was measured based on structural and behavioral validity tests. The results showed that due to changes in performance, the cost of implementing changes in a system varied in terms of cycle and in the later stages, the cost of development increased. This delay also increased costs and reduced development productivity. Moreover, the simulation illustrated that process agility helped complete more tasks at a lower cost. The dynamics model developed in this research can be used as a tool by an organization to understand and analyze the effects of different rapid development practices and supply chain management strategies.

In this research, considering the importance of the topic and the gap in previous researches, a model for predicting tax evasion of guilds based on data mining technique is presented. The analyzed data includes the review of 5600 tax files of all trades with tax codes in Qazvin province during the years 2013-2018. The tax file related to guilds is in five tax groups, including the guild group of owners of official offices, the guild group of real estate consultants, the guild group of catering halls, restaurants and related businesses, the guild group of communication services, and the guild group of showrooms and auto accessories stores and related businesses. The decision tree classification model was used for modeling. The results show that the decision tree model based on the available data is considered a suitable model for prediction. The coverage criterion is 68%, the Kappa criterion is 0.612, which shows the good performance of the modeler. Also, using the Cross Validation technique, the validity of the prediction model was tested in order to more reliably estimate the percentage of modeling performance. The accuracy criterion equal to 67.79% shows the appropriate reliability for the prediction model. The results of this research can be used in formulating operational strategies based on data mining to predict the tax evasion of guilds in the provinces.

This paper aimed to design a robust blood supply chain model that includes the stages of collection, processing and distribution of blood and blood products taking into account the lifespan and age of demand, which seeks to reduce supply chain costs and reduce the shortage and waste of blood products.

In this paper, MINLP method is used to model the research problem and in order to face the uncertainty in the problem parameters, the MPFRP method based on fuzzy data is proposed. The designed model was first evaluated for validation with numerical examples in small and large size and using real data in a case study in GAMS software?

Using numerical examples and real data, the output indicates the performance of the proposed model. The output also had acceptable flexibility in the face of uncertainty in the parameters of the research model.

Originality/Value:

 In this study, in order to reduce the shortage of blood products in situations where blood product is not available in the same group as the requested blood product, the ABO-RH adaptability principle has been used to replace the received demand with a compatible inventory. And also, to deal with uncertainty in uncertain parameters in the supply chain a solution based onmixed possibilistic-flexible robust programming is proposed.

Companies' efforts to gain more market share and maintain survival have made the integration of companies to use each other's ability as a parent company. One of the main concerns of the parent company is how to control the subsidiary businesses. The present study has been carried out by purpose of design an intelligent model for corporate control strategies with emphasis on the interaction of the parent company with subsidiaries in Holding TAPIKO. This research is applied in terms of purpose and in terms of method, descriptive-follow-up research. Research data includes documentation received from literature and indexed articles in Scopus and Science Direct, as well as semi -structured interviews. First, using qualitative content analysis methods of interviews and articles were coded in maxqda2020 software, 28 sub -categories in the form of 8 short -term profitability categories, long -term profitability, distinctive capability, market trends, fitness, company size, power size, power Politically identified. The following comments were used to identify the coefficients of the importance of components and write fuzzy rules, and were designed using MATLAB software and fuzzy inference system (FIS), which included 31 fuzzy rules. The model was implemented in 3 modes of cellulose, tires as well as petrochemicals. The results of the research for cellulose and tire companies indicate less financial control strategy and interference, and for petrochemical subsidiaries, it shows strategic control and greater interference by the maternal firm. The result of validation review through Surface analysis also indicates the appropriate model validity of the model.

This study aims to design a humanitarian logistics network for location-routing equipped with drone-enabled delivery systems under uncertainty conditions. Here, we divided the model into two phases including pre- and post-disaster. There is an important question in pre-disaster phase: Where the central warehouses better perform to minimize the cost and time? To this end, the logistics problem represented by the transportation of relief products was modeled as a Multi Echelon Multiple Depot Vehicle Routing Problem (MEMDVRP). For solving this mathematical problem, the presented model was initially solved using meta-heuristic algorithm of Non-dominated Sorting Genetic Algorithm III (NSGAIII) in large dimensions and sensitivity analysis was performed on its effective parameters via MATLAB software. Due to the scenario nature of the problem, 4 scenarios were considered in the model and then were compared separately for each goal. Given the results, scenario 4 showed the best situation in terms of benefits maximization. Regarding the cost, scenario 4 shows the worst status and the scenarios 1 and 2 revealed the best status. It should be noted that due to the nature of cost minimization objective, the lower this value, the better the result, indicating the best cost situation for Scenarios 1 and 2 and the worst for Scenario 4. In terms of time, Scenario 4 indicated the worst condition likewise the cost. Interestingly, regarding the benefits, the Scenario 4 leads to the most benefits, so it can be said that in this scenario, as the benefits increase, the cost and time also increase, suggesting a conflict in objectives.

In present study, a mathematical model for designing a humanitarian supply chain network and vehicle routing problem considering cross-dock is proposed where a Non-dominated Sorting Genetic Algorithm (NSGAIII) is used for implementing the proposed model in a large-scale problem. Since the model was implemented in a large-scale case, various sensitivity analyses were performed to extract the results. Hence, the results showed that the costs have more effect on the first objective function (patients compared to total injuries) and the second one (shortage), respectively. Compared to the other two objective functions, the impact on the cost function is negligible. The effect of transportation cost of relief goods/supplies from the supplier to the warehouse on the first objective function is higher than the others; however, the effect of this cost is further than that of the cost from the supplier to the distributor, accordingly, in comparison to the previous cost, the output reacted more to this cost. The transportation cost from the distributor to the warehouse (cross-docking) has less effect on the cost function unlike the transportation cost from the supplier to the warehouse. Nevertheless, the result shows that an increase in the cost can lead to a considerable increase in the ratio of patients to total injuries as well as shortage. In other words, the objective functions would deteriorate when this parameter tends to be increased.

Although the expansion of parent firms is of great importance to economic development and their central role in the administration of diverse businesses and value creation is undeniable, one of the main concerns of these firms and managers of subsidiaries is how to establish relationships or in other words corporate control. Parent firms can control the entire business process of subsidiaries, and this control can be introduced in the form of three styles of strategic planning, financial control and strategic control, which is commonly known as parent control in theoretical literature. However, the complexity of environmental conditions and increasing uncertainties will not allow the adoption of a fixed control style to meet the goals of the parent firms. Therefore, creating an interactive and scenario -based control system is recommended for subsidiaries for long-term survival. In this article, by reviewing the literature on parent firms control and a critical view of the popular methods and styles of controlling  subsidiary companies, a new method with an emphasis on participation, interaction and internalization of strategic decisions is presented to cover the current shortcomings and offer a more effective control of firms in changing environments. In the current study, the different categories of parent firms along with their configuration and managerial styles under different conditions, the proportion of characteristics, size, diversity and value -making practices are explained and compared. This review article can be effective for corporate control and can open a new horizon for future researchers to analyze the different styles of parent firms under uncertainty.

In this research, considering the importance of the topic and deficiency in previous researches, amodel for predicting tax evasion of guilds based on data mining technique is presented. Theanalyzed data includes the review of 5600 tax files of all guilds holding tax codes in Qazvinprovince during the years 2014-2019. The tax file related to guilds is in five tax groups includethe guild group of owners of notary public offices, the guild group of real estate agencies, theguild group of catering halls, restaurants and related businesses, the guild group ofcommunication services, and the guild group of exhibitions and auto accessories stores andrelated businesses. For modeling, the classification model including the decision tree algorithmwas used. The results indicate that the coverage criterion is 68%, the Kappa criterion is 0.612,which indicates the good performance of the modeler. Also, using the Cross Validationtechnique, the validity of the prediction model was tested in order to more reliably estimate thepercentage of modeling performance. The accuracy criterion equal to 67.79% shows theappropriate reliability for the prediction model. The results of this research can be utilized informulating operational strategies based on data mining to predict the tax evasion of guilds in theprovinces.

The purpose of this article is to study the factors affecting the supply chain of parts and equipment of the oil industry under uncertainty, and to examine the influence of the factors of the supply chain model under uncertainty on each other and to provide practical solutions. Therefore, according to the hybrid approach, to explain the supply chain model of oil industry parts and equipment under uncertainty, in the qualitative part, the grounded theory method was used and in-depth interviews with 15 experts (managers, experts and suppliers active in the parts supply network and equipment of oil companies) were done. This model consists of six main themes: 1) causal conditions (supply factors, disruptions, macroeconomics, laws and policy and security); 2) underlying conditions (process complexity and environmental complexity); 3) Intervention conditions (organizational resources); 4) category</em> </em>oriented (decision maker); 5) Strategies (management practices strategy, management strategy, adaptive strategies); 6) Consequences (advanced measurement, advanced configuration, advanced exploration and advanced operation). Then, in the second step, using the technique of confirmatory factor analysis and modeling of structural equations among 120 managers, experts and active suppliers, the resulting model was fitted, validated and tested.</em>

The green human resource management is a new management philosophy based on the green movement in relation to the protection of our environment and a model in which the concept of green is used in the field of human resource management. The present study was conducted to identify and rank the priorities of green human resource management. The method of this research is descriptive survey and the statistical population included twenty professors of Shiraz University of Medical Sciences. In this regard, a pairwise comparison questionnaire was developed and distributed among research experts and then collected using Expert Choice software. AHP and fuzzy Delphi techniques were used to rank the antecedents. Findings showed that organizational factors with a weight of dimensions of 0.627 were ranked 1st and among its components, the quality of human resources with a weight of 0.359 was ranked first. Technological factors with a weight of 0.289 dimensions were ranked second and its advantage component was ranked first. Environmental factors with a weight of dimensions of 0.084 ranked third and among its components, government support with a weight of dimensions of 0.336 was ranked first. The overall findings demonstrated that organizational factor was ranked first in terms of importance, technology factor was ranked second and environmental factor was ranked third in terms of weight.

Most parts of Iran have arid and semi-arid climates. Therefore, many deserts and playas have been formed in these areas. In the present study, the return of saline water due to the groundwater head increase in the aquifers with the usage of SUTRA numerical model, was investigated. In order to assess the wedge behavior of saline water in transient state, the toe length of the wedge is analiezed. The changes in the hight of wedge shape due to the time is measured.  The results showed that: a) with the progression of the wedge behavior, its height is getting earlier to the steady state in comparison to its length, however in the return time, they both reached the steady condition at the same time. b) Unlike the wedge's length, which reachec the steady state earlier than the progession time, its height has an equal time to reach the steady condition in both states (progression and return). The achieved results also showed that due to the mixing processe, the mixing zone expanded earlier in return phase. Also, as the wedge approached the steady condition, the area of mixing zone decreased gradually.

the purpose of this article was to investigate green human resource management activities, effective factors, and their consequences in government organizations.

To achieve the purpose of this article, a qualitative research project was selected and the dimensions, components, and indicators of the green human resource management model were identified using the meta-combination method and theme analysis. Then the identified dimensions, components, and indicators were validated using the fuzzy Delphi technique.

The results of the meta-combination led to the identification of the dimensions of leadership, technology, budget, and culture as prerequisites for the establishment of green human resource management. The dimensions of recruitment, training, performance appraisal, and compensation of green services were identified as the executive processes of establishing green human resource management. Finally, the dimensions of economic, social, organizational, and environmental consequences were identified as the consequences of the establishment of green human resource management.

that green human resource management activities can have positive consequences for the development of Iranian government organizations, this article was conducted to identify the prerequisites, processes, and consequences of establishing green human resource management in government organizations and led to the design of a model in this regard.

The purpose of this study is to identify and determine future organizational strategies in the Imam Khomeini Relief Committee.

In terms of methodology, it is a combination (qualitative - quantitative) study. In the first stage, organizational strategies were extracted by grounded theory method through open coding, axial coding and selective coding and then were confirmed after accreditation by nine experts of university professors. In the second stage, using Dematel technique, the causal relationships, effect, influence, direction and intensity of the effects were identified.

The evaluation of Dematel technique has shown that the e-government development strategy is the most effective and the promotion of administrative health is the most effective. Productivity promotion strategy (organization and human resources) among the eleven research strategies has the most relationship or interaction with other strategies. Also, out of eleven strategies, four strategies are causal variables and seven strategies are disabled variables.

The research findings show that the four strategies of streamlining the administrative system, developing e-government, improving productivity and economizing the services of the organization as causal variables are the most effective strategies that help the Imam's Relief Committee in the future. Through them, it can effectively manage the deprived and the needy. Accordingly, the researcher has localized these strategies by segregating and nationalizing organizational strategies, and has determined the most compatible strategies for managing public organizations in the future by influencing and designing an appropriate impact map between the strategies.

The competence of managers, especially at senior levels, is the basis for the success of companies and the development of the country. Corporate governance as a set of principles, requirements and processes for monitoring and governing the company has been notified to the governmental companies by the relevant authorities and its executors are senior managers (members of the board of directors); Therefore, designing the competency model of senior managers according to their role in the optimal implementation of corporate governance is the goal of this research.

This research is developmental in terms of purpose and mixed (qualitative-quantitative) in terms of data type and method of analysis. In the qualitative section, by studying the background and theoretical foundations, the dimensions of competence and the components of corporate governance were identified. Eleven members of the board of directors of governmental companies in various fields of production, services and investment, and selected academic experts were interviewed, and by content analysis method, the themes were identified at three levels: basic, organizer, and comprehensive. In the quantitative part, structural-interpretive modeling, leveling and determining the relationships of the components and dimensions of the model were performed.

The findings of the qualitative section were obtained by combining theoretical studies and content analysis of interviews, 55 basic themes (index), eleven organizer themes (component) and three comprehensive themes (dimension). The dimensions of the model include knowledge, skills and character. 

Based on the results of quantitative analysis of the research, the main components of the competency model are classified into four levels. Dimensions of character (including moral virtues, personal characteristics and values) are the most effective role models and guider of other components. All the main components have two-way influence on each other. The output of the study led to the design of a competency model for senior managers of governmental companies with a corporate governance approach.

One of the ways to acquisition a competitive advantage is the tendency toward strategic innovation; because innovative products provide valuable opportunities for long-term growth and survival of companies. Researches has shown that strategic learning and strategic flexibility with the prospective view can improve strategic innovation. Therefore, the purpose of this study was to present and test the structural model for examining the effect of Collaborative Open Foresight on Strategic Innovation with regard to the mediating role of strategic learning and strategic flexibility in aviation industry.

This research is a cross-sectional study in terms of type of use, and descriptive-correlational in terms of data collection, and based on structural equation modeling and cross-sectional study in terms of time horizons. The statistical population consisted of 430 executives of selected active companies in the aviation industry and with Simple random sampling, 229 people was considered as a statistical sample. Data were collected by structured questionnaire and analyzed by structural equation modeling and LISREL software.

The results of data analysis show that collaborative open foresight, directly and indirectly due to strategic flexibility and strategic learning has a positive and significant effect on strategic innovation.

According to the technology-based and nature of corporate cooperation in the in the aviation industry, promotion of strategic innovation depends on strategic learning and strategic flexibility, which is obtained by collaborative open foresight.

Having the exact values of boundary conditions is one of the effective way to accurate groundwater models. In the present study, the exact value of constant head boundaries in Birjand aquifer is specified with the usage of particle filter linked to meshless groundwater model. Particle filter known as one of the data assimilation methods applies to dynamic systems in order to improve their performance. Meshless model, one of the numerical models that do not mesh the problem domain, enforces the governed equation to nodes. Birjand aquifer with almost 269 km2 area, has 190 extraction and 10 observation wells. There are also nine inflow and one outflow regions with constant head boundary conditions, which include 105 boundary nodes. After determination of the lower and upper bounds of groundwater head for each node, the exact values of this parameter is computed. Finally, the simulated groundwater head compared with observation data. The closeness of the achieved results to the observation data showed the performance of the engaged method, as the results indicated a significant decrease in RMSE occurs just with the usage of particle filter linked to meshless model. RMSE value reduced to 0.386 m as its previous value was 0.757 m. The results also showed that the model was more accurate when the number of particles in particle filter increased. The RMSE value for 500, 700 and 1000 particles were 0.484, 0.401 and 0.386m respectively.

In recent decades, researchers are turning to the potential of ABMs to study complex phenomena. Due to intrinsic interconnections, structural interactions and inter-dependencies, individual variations, and communications of various components, supply chain network should be accordingly treated as a complex adaptive system. ABM is dominant tool exploring the emergent behavior of supply chain network with numerous interactive agents. This paper aims to conduct a systematic literature review on the agent-based modeling in the concepts of supply chain and various fields of research. Using reputable databases, combining intended keywords and applying filters based on restrictions and indicators, a total of 123 relevant articles are selected from the valid journals and conferences in year 2010-2019, and 17 subjects in association with supply chain management and 23 subjects related to other fields are presented. Moreover, a brief history and the definition of the three basic areas including complex systems, complex adaptive system and agent-based modeling are provided. The main objective is to provide a perspective based on agent-based modeling and complex adaptive systems for researchers in different sciences and especially supply chain researchers, who are not sufficiently familiar with the philosophy and applications of these approaches.

The present study aims at designing a cold multi-cycle supply chain based on a multi cross-dock system taking into account uncertainty. In the first step, we identified the factors and variables of the model. In the second, by selecting the study period through designing data collection forms and using the documents reviewing methodologies, the raw data required to measure the final indicators were collected and processed in the project model. Then, they were analyzed considering the research topic and using the techniques of genetic algorithm and particle swarm optimization. The primary objective function is minimizing the cost of transportation and warehousing throughout the supply chain, the second minimizing the total operation time and the number of vehicles within the supply chain, and the third maximizing the product freshness time. Also meta-heuristic optimization methods (strongly adjustable) were adopted to deal with the travel time of suburban vehicles. We also provide an example of the performance of optimization models for a small-sized sample. The computational results showed that longer travel time and further distance do not necessarily increase costs. In fact, it is possible to distribute the products with the right number of trucks at an optimal cost at the right time.