جستجوی مقالات مرتبط با کلیدواژه « برنامه ریزی آرمانی » در نشریات گروه « مدیریت »

AbstractIn today's global competition, choosing suppliers, increasing relationships with suppliers, and developing collaborative and sustainable relationships with them to reduce costs and increase flexibility against market changes is necessary and difficult. The present study aims to design a model for ranking suppliers and allocating the optimal number of purchases of sugar beet from the suppliers. The statistical population of the research is experts and specialists in the field of supplier selection at Torbat-e Heydarieh Sugar Company whose number is about 10 people based on proficiency, authority, and skills. The research method of this study is quantitative based on nature, and applicable based on purpose. In this research, to identify the basic criteria for the selection of suppliers, theoretical literature and experts' opinions have been used, and the method of the Analytic Hierarchy Process has been used to rank suppliers. In addition, to allocate the optimal order amount to each of the suppliers, the integration of the Goal Programming model with the Analytic Hierarchy Process has been used. The results of this research show that how Torbat-e Heydarieh Sugar Company can allocate optimal order amount to any of the suppliers by prioritizing them and also by examining the different parameters, according to the capacity of suppliers, and determine how the studied companies purchase their desired raw materials from suppliers to achieve the desired relative and strategic advantage.ExtendedIntroductionThe issue of supplier evaluation and achieving sustainability in the supply chain is one of the important components of supply chain management because suppliers play an important role in creating sustainability in the supply chain, which means achieving social, environmental, and economic goals and ultimately the success of the company. As much as the selection of suitable suppliers is effective in reducing costs and increasing the competitiveness of companies, the selection of inappropriate suppliers can also degrade the financial and operational position of companies (Baroto et al., 2022; Soheilifar and Falah Lajimi, 2019). The process of selecting suppliers is the most important factor in the effective management of the modern supply chain network because it helps in achieving high-quality products and customer satisfaction. Also, the performance of the supplier plays a key role in price, quality, delivery, and service in achieving the goals of the chain (Mohammed  et al., 2021; Tavakolian et al., 2020).Currently, the way to supply raw materials and evaluate suppliers in the supply chain is one of the challenges that organizations face for more profitability. Because of the ever-increasing number of suppliers due to the creation of competitive conditions, organizations need to develop a suitable methodology for evaluating and selecting suppliers as well as evaluating their performance to successfully reduce costs and increase the quality of services and products (Rashidi Komijan and Masoudifar, 2021).On the other hand; if the supplier cannot deliver the orders on time and with the required quality and reliability, issues and problems will arise in meeting the demand of the seller's customers and ultimately lead to customer dissatisfaction (Ha & Krishnan, 2008). A supplier that fails to deliver a guaranteed and sufficient product to the seller on time will result in customer loss (Gupta & Barua, 2017). Therefore, choosing a supplier is of considerable importance. During the process of choosing a supplier, especially in a competitive environment, it is very important to buy from a supplier who can meet the most criteria such as material quality, on-time delivery, etc. The current research aims to provide a multi-stage and consistent approach for selecting and ranking effective factors and providing a model for the best purchasing situation using the Goal Programming method, which initially identifies the effective criteria for the evaluation and selection of suppliers and the desired criteria using the hierarchical analysis method, then the important suppliers of Tarbat-e Haidarieh Sugar Company have been ranked and finally, the optimal amount of purchase from suppliers has been allocated using the AHP-GP mixed model.Theoretical frameworkRashidi Komijan and Masoudifar (2021) in a research titled "Mathematical model for evaluating suppliers and purchasing spare parts" showed that determining the group for each part according to the two dimensions of supply risk and criticality of the part is a suitable management tool for equipment supply management, and the use of the zero and one planning model is a suitable method for allocating orders in the field of spare parts, and the structure and components of the objective function and restrictions can be changed according to the type of organization.Firouzi & Jadidi (2021), in research entitled "Multi-objective model for supplier selection and order allocation problem through fuzzy parameters", presented a fuzzy multi-objective model for the supplier selection problem and have created a weight additive function to convert the fuzzy multi-objective model into a single objective fuzzy model that can effectively consider the preferences of decision-makers. Then, a separation method was used to solve the single-objective model with fuzzy parameters (Firouzi & Jadidi ,2021).Naqvi & Hassanzadeh Amin (2021) have written an article titled "Supplier selection and order allocation: a literature review." In this research, the articles conducted in the field of supplier selection have been reviewed, and the scope of the problem has been examined in three subcategories, including literature models, deterministic optimization models, and uncertain optimization models.MethodologyThis research is applied based on the purpose, and descriptive-survey based on the nature and method of research. Data collection has been done through interviews and distribution of questionnaires among senior and middle managers and experts involved in the purchase of beet sugar of Torbat-Haidarieh sugar factory. Also, through library studies and the use of references and sources related to the topic, the materials and topics related to the discussion have been extracted and used in the present research. The aim of this study is to provide a multi-stage and consistent approach to select the effective factors, rank them, and then provide a model for the best purchase situation using the Goal Programming method. This methodology can be divided into two main phases: the first phase includes the determination of quantitative and qualitative criteria and the use of an Analytic Hierarchy Process to weigh the criteria and options, and the second phase includes the identification of goal and systemic limitations and combining the results of the first phase with the Goal Programming method to allocate the optimal order amount to each supplier. The softwares used in this research were Expert Choice and Lindo 6.01.Discussion and ResultsThe purpose of this research is to provide a framework for the analysis and selection of suppliers of raw materials for Torbat-Haidaryeh Sugar Joint Stock Company. Therefore, this research provides a framework that determines the optimal combination of suppliers according to multiple quantitative and qualitative goals and takes into account system limitations so that the maximum possible value is achieved according to the opinions of experts and specialists of the company. One of the features of this research and the combined model is the possibility of considering the weight of decision-makers. This is important because the decision-making committee may include different members, each of whom has different positions in the organization. By accepting the assumption that different positions are the result of knowledge, experience, work records, etc., the executive director as the person in charge of the decision-making committee can compare the members of the committee in pairs, and finally, the weight of the decision-makers is obtained by calculating the special vector of the matrix. Then the next calculations will be influenced by the weight of the decision-makers. In this study, the factors influencing the selection of suppliers were first identified using literature and experts' opinions. Then these criteria and sub-criteria were prioritized using the AHP method. After that, each of the suppliers was rated for each criterion and also for all sub-criteria. In the next step, using the Goal Programming method, the optimal amount of order allocation to each supplier was determined, and according to the results of the research, the largest amount of purchase allocation should be made from Razavi Agricultural Company; Islamabad and Khezri Agricultural Company in the second place, and Marghzar Farmers’ Cooperative Company were ranked third according to the number of orders. Among the other advantages of this model, it can be mentioned that this model includes multiple criteria (quantitative and qualitative) such as grade, quality, timely delivery, etc. in the evaluation and selection of suppliers so that the optimal value according to the Goal limitations is allocated to selected suppliers.ConclusionAccording to the results of this research, at first, the effective components on the evaluation of suppliers were extracted based on the opinion of experts and theoretical foundations. After that, these components were prioritized. After prioritizing these components, all suppliers were evaluated based on these components. Finally, after prioritizing the suppliers based on these components, the optimal allocation of orders from suppliers was determined for each supplier. Among the evaluation components, shipping cost is one of the factors influencing the order (Gergi̇n et al., 2021; Jiang et al., 2018; Adalı & Işık, 2017) and most companies are formed near raw materials to bear the least excess cost. (Khan et al., 2016). Also, companies are generally looking for suppliers who can be more compatible with these companies in terms of conditions (Hadian et al., 2020; Gergi̇n et al., 2021), but in some situations, such as the lack of primary goods and the presence of strong competitors, the supplier gets a higher bargaining power and in this situation, the company has to adapt reluctantly to the supplier's conditions (Mohammed et al., 2021). In this situation, companies may have financial requests in the implementation of the contract (Öztürk & Paksoy, 2020). The more financially powerful the suppliers are and the more they can supply, the more they can change the conditions in their favor. On the other hand, the fewer competing companies in the market, the more companies can choose their suppliers with better conditions (Taherdoost and Brard, 2019). Governments can push companies to buy more products from suppliers by giving subsidies. However, companies tend to buy from suppliers with higher quality products (Rezaei et al., 2014; Adalı & Işık, 2017).The higher the quality of the products, the more companies look for the products of these suppliers (Fei et al., 2019). On the other hand, one of the most important factors for sugar beet companies is the grade of this product, and the companies have understood very well that products with higher grades lead to more profit for these companies; therefore, they are looking for buying quality products with suitable quality. Reassuring factors are among the factors that are of great importance in the process of supplier evaluation and selection. Suppliers whose delivery is fast and on time are more important for companies (Jain et al., 2018; Arabsheybani et al., 2018); because if the delivery time is inappropriate, it may cause problems for the company's production. In addition, suppliers who have stable delivery guarantee the future of the company's production (Hadian et al., 2020), and these suppliers are considered strategic partners of the company and are generally much easier adapt with the Companies' conditions to conclude a contract (Szmelter-Jarosz, 2020).The company should support its loyal suppliers and not leave them alone in critical situations, and the contract between the two should be designed in such a way that the risk is shared between the supplier and the company to create confidence on both sides of the transaction (kabgani & shahbandarzadeh, 2019; Junior et al., 2014). Due to the fact that in this research, the mentioned cases have been investigated, therefore, this research is in accordance with the research conducted in terms of using the mentioned variables. In this section, according to the results of the research and in line with expanding the scope of the dynamic problem of supplier selection and order amount allocation, it is suggested that from now on, using the results of this research, the selection of suppliers in this company to be done every year by systematically and scientifically collecting the information required by the models, and establish a marketing strategy related to the suppliers who have obtained high ranks in this research. Also, considering that the conclusion of the initial contract is the responsibility of the company's inspectors; a list of factors affecting the selection of suppliers based on the set priorities has been provided to each of the inspectors to identify the suppliers based on it and proceed to the final negotiations. After the ranking, it was found that the sugar beet quality criterion has a very important priority among the factors. Therefore, it is suggested that sugar production companies use the quality determination device (Betalyzer) to determine the quality of beet sugar.

Today, the digital gaming industry has a significant impact on the economic, cultural, and social spheres around the world. The advent of real and virtual reality games, particularly in medical science, has taken this industry out of the realm of mere entertainment and has become one of the applied industries. This study aims to optimize the combination of indigenous digital game development strategies, using a goal mathematical programming model. Compared to other common methods, the proposed approach can be a good alternative to studying and using mathematical planning in strategic management, when strategies are evaluated and selected.

Design/methodology/approach:

 The research method of this study is typically mixed qualitative and quantitative for which, the main data were collected using library studies and theoretical framework review, in-depth and structured interviews with 12 experts and specialists in the digital games industry. A filled questionnaire was collected after coding variables. Thematic analysis (reasoning and rational analysis) was used to extract and classify the components. Also, an integration of House of Quality (HOQ), Analytical Hierarchy Process (AHP), and Simple Additive Weighting (SAW) techniques were used to determine the variables and parameters required in the mathematical model of the research. Finally, a goal programming model was used to determine the optimal combination of the strategies.

A portfolio of optimal strategies was proposed that were effective in removing barriers and challenges in the game industry, which facilitated the achievement of game development goals with desirable capabilities in implementation. The mentioned strategies were capabilities empowerment and development of game-making experts, targeting and enriching the content of homemade games, financing and facilitating investment, and increasing the level of competitiveness of game-making groups.

Research limitations/implications: 

The limited number of expert group members and the researcher's low access to them, in addition to creating problems related to the distribution and collection of questionnaires, review and increase the computational accuracy of validity and reliability, and also calculating the compatibility rate in the pairwise comparison questionnaires were the challenges and limitations of this study.

Practical implications:

 The digital games industry has a great potential for growth and development, and its favorable economic, cultural and social effects are undeniable. Some of the practical findings of this study are the creation of an elite network and a strong relationship between gaming enthusiasts and the university, empowerment of game developers' knowledge and game studios in the gaming ecosystem, and monitoring and support of governmental and non-governmental policy-making institutions.

Originality/value: 

In this paper, a new approach was proposed for evaluating and optimizing strategies for developing indigenous digital games to overcome their challenges and meet the relevant objectives in compliance with their feasibility (ease) of implementation. Also, the use of mathematical modeling in evaluating and selecting optimal strategies in this industry distinguishes this study from the literature.

The purpose of this paper is to evaluate the efficiency of decision-making units using the goal programming model of data envelopment analysis with restriction weight and ranking of units with a unique method in Ghavamin Bank.

In this study, the classical CCR model was used to determine the management efficiency of provincial branches in Ghavamin Bank. To increase the discriminative power of efficient and inefficient decision-making units, a combination of goal programming models with Weight restriction was used and a new model called goal programming of data envelopment analysis with Weight restriction was presented.

Based on the output values of the classical CCR model, 16 out of 32 decision-making units became efficient and 16 units became inefficient. In the next step, for more separability of the units, the goal programming model of data envelopment analysis with Weight restriction was used. The results of the first-order Euclidean norm became 7 efficient and the rest inefficient out of 32 decision-making units, and the results of the infinite Euclidean norm became 1 of 32 efficient units and the rest of the decision-making units inefficient.

The results showed that the goal programming model of data envelopment analysis with Weight restriction related to infinite Euclidean norm in separating and ranking efficient decision-making units from inefficient has a high discriminate power compared to the classical CCR model and the first-order Euclidean norm.

This study aims to propose a multi-objective model for determining reliable suppliers of one-shot systems. Design/methodology/approach: First, based on the evaluation indicators, the risk of each supplier is estimated. The subsets’ risks are also evaluated using the causal-effect matrix. Considering possible events for the one-shot case and analyzing a fault tree led the researchers to meet the best composition of equipment. 

The proposed model is capable of leading practitioners to allocate suppliers effectively when a one-shot case is considered. Research limitations/implications: The results of this study are referred to the current equipment of the focused one-shot system. Also, the results are limited to potential risks identified, evaluations related to comments, and the proposed model for the considered time interval. 

Based on the findings, applying the proposed approach can lead to an effective management tool for selecting suppliers with acceptable risk in one-shot systems.  

A one-shot device is defined as a unit that can be used only once, hence the device cannot be used for testing more times. Each subset used in one-shot systems, regardless of how it supplies, has a specific risk level. Depending on what any subset provides, it also affects the factors influencing the overall system failure. Therefore, selecting appropriate suppliers is significant to ensure correct function of a system. 

The proposed model can be used as a fast and reliable method for determining appropriate suppliers for one-shot systems, whose results can be relied upon with a suitable approximation in respect of the sensitivity analysis. To the best of the authors’ knowledge, nobody else have addressed the problem in such a way.

This paper proposes a bi-objective mixed-integer linear programming model for formulating a lot- sizing and scheduling problem for the perishable yogurt industry under demand uncertainty. The objectives of the proposed model are to simultaneously minimize the overall cost and the total production completion time.  The proposed MILP formulation integrates many distinctive features of yogurt processing, including shelf-life constraints, setups, packaging rates, minimum and maximum lot size limits, future time for holding products, and fuzzy demand. Additionally, the proposed model, including inventory control, is a multi-product and multi-period model hence, it is categorized as an operational-strategic model. We introduce a hybrid approach focused on fuzzy possibility programming and a fuzzy goal programming approach for solving the suggested bi-objective model, where possibility, necessity and credibility measures are adopted according to the decision makers’ preference.  Compared to the traditional model of lot sizing and scheduling, better decision-making and sensitivity analysis for DMs can be made based on the three obtained efficiency values. Data from the yogurt plant were used to assess the feasibility of the proposed model and solution approach. The results obtained from applying the method and sensitivity analysis showed the effectiveness of the mathematical formulation as well as the proposed solution method.

Terminals are major urban passenger centers that play an important role in collecting demand and distributing it on the network. The proper functioning of terminals depends on their proper planning, an important part of which is devoted to their principled location. The issue of locating intra-city bus terminals should be considered as optimization issues.

 The mentioned method is based on four consecutive stages, according to which, in the first and second stages, the candidate points for the construction of intercity bus terminals are selected according to the network of bus lines and the location of the lanes, as well as according to the existing terminals. In the third stage, the cost of construction and acquisition, the value of access to adjacent uses, as well as the amount of coverage that each candidate points provide in the city, are evaluated. Finally, in the fourth stage, the problem is transformed from a multi-objective mode to a single-objective maximization problem using the ideal planning method, as a result of which the top points are identified among the candidate points. In order to better understand the proposed method, the problem of locating terminals was implemented in the city of Shiraz, which finally selected the proposed 3-point algorithm as the final points for the construction of intercity bus terminals.

Examination of the results of the model and parameters of selected points shows that these points are among the important and effective points for the construction of the terminal and are relatively in good agreement with the policy of Shiraz Municipality Bus Organization in locating the terminals.

Originality/Value:

In this paper, an innovative method is used to solve the problem of locating terminals, which strengthens the existing knowledge.

The purpose of this study was to determine the comprehensive performance evaluation criteria to improve the performance evaluation system of employees using a new model of data envelopment analysis based on 360-degree evaluation for employee ranking.

In this study, first, performance evaluation criteria were identified by studying the research background. Questionnaires designed based on the opinions of twenty-five staff of the organization, three senior managers, ten professors with university experience and ten active and selected students of the university (a total of 48 people in a 360-degree structure) are completed and then using A new model of designed data envelopment analysis, employee ranking, was performed. Twelve performance evaluation indicators extracted from the research background by experts in four categories with the titles of service compensation system in the first category; Job security, perceived organizational justice, perceived organizational support, and physical working conditions in the second category; Job characteristics, job clarity and ability of employees in the third category and job feedback, job stress, organizational citizen behavior and motivation in the fourth category were ranked and documented using a linear optimization model based on the goal programming and policy. Data envelopment analysis resulted in a complete ranking for the staff of a university unit with 25 staff members.

Interpretation and analysis of structured results obtained from the use of data envelopment analysis policy based on 360-degree evaluation can be the basis for improving human resources and continuing periodic evaluation to continuously improve employee performance in the organization.

Originality/Value:

The present study can help their evaluations by using various indicators comprehensively as well as 360-degree approach and considering the external and internal challenges of the organization.

Nowadays, production of economic production is one of the most important of policymaker’s tensions. Address to this. It is necessary to merge the farmer’s aims along policy makers as well as their necessities. Therefore, the current study attempted to investigate on optimum cropping pattern of agricultural crops in Kurdistan province respect to each county emphasizing on minimize virtual water. To follow research aim the necessary data were collected for the agricultural year 2015-6 using goal programming. The results showed that, the current cropping pattern does not has no comparative advantage and it has to experience significant change. In other words, the current cropping pattern willing must to change from mixed form to specialized one according to comparative advantage according to resource possibilities of each district. The range of change showed that, there are significant decrease and increase in some crops compare to current situation. The results showed that, irrigated wheat did not get permission to enter optimum model. In addition, the most of current crop due to low return as well as disadvantage of study area omitted in recommended pattern.

Using the data envelopment analysis method to determine the most efficient companies listed on the Tehran Stock Exchange.

In this study, three industries of banking, petrochemical and pharmaceutical have been studied to determine efficient companies. Then, using the ideal planning method, the investment percentage of each company's share in the portfolio is calculated. In this method, once the return and share risk as model variables and with another liquidity variable is added to them.

The results showed that after ranking the companies, their sensitivity can be analyzed and by determining the weaknesses and recognizing the impact of variables, to increase the efficiency of companies.

Originality/Value:

Using the portfolio of efficient companies for investment leads to reducing investment risk and choosing the right portfolio.

Startup accelerator program is a new incubation model to accelerate venture creation providing specialized mentorship, networking opportunities and financing growth driven businesses. Since emergence of the first accelerator in US in 2005, the number of seed accelerating programs has quickly grown worldwide. Performance evaluation of these emerging programs not only could clarify relative success of this new incubation approach but also help out Iranian emerging accelerators to benchmark from pioneers of the industry. The evaluation could also assist startups and entrepreneurs to find out which of the existing accelerators are well-performed and thus ease decision making to select them as their incubator. So in this paper we aim to measure the performance of US top accelerators using a DEA method combined with goal programing approach. The inputs of the evaluation consist of numbers of mentors and startups, investment on each startup in average and in general, and the share of accelerator in startup company. The outputs in turn are different and include number and value of exits, and fund raising. Comparison of the final result with Seed Accelerator Ranking Project (SARP), shows different sorting and it is due the distinct evaluation approach. SARP considers only outputs of accelerators but we take in to account both outputs and inputs in the evaluation which could better illustrate the efficiency of DMUs.

Investment management in life insurance is very important because of its specific features. Unlike other insurance policies, life insurance is long-term and focused mainly on return on investment. Also, due to the 85% participation of insurers in the surplus of interest, the surplus in a period has little income for the insurance company,but the insurance company has a guaranteed return on the deficit. In addition, high return is one of the main factors of insurance companies competition in marketing. Also, insurance companies need to make sure they have enough liquidity to fulfill their obligations. Despite the fundamental differences between life insurance and property and liability insurance, No 60 Central Insurance Regulations do not differentiate between the investment of the above insurance reserves. In this study, we designed a portfolio optimization model for life insurance investments. Accordingly, the Markov Switching Vector Auto Regressive based on ideal optimization with contrasting goals set with the actual performance of the company. Optimization has been made in the portfolio of life insurance based on Moalem Insurance Company from 2012 to 2016. Investment weights have been implemented by simulating the Markov Switching VAR model with optimization objectives including maximizing insurance returns, minimizing shortfall, maximizing policyholder returns and minimizing liquidity shortages. Based on the results, the ideal planning optimization model produces more returns than the actual returns of the insurance and performs better in other objectives. As a result, this approach can be used to optimize life insurance investment portfolios in insurance companies.

With increasing environmental pollution in recent years, researchers have focused on designing a closed loop supply chain network with consideration of environmental issues. In this research an uncertain bi-objective, multi-period, multi-product and multi-level closed-loop supply chain network is presented. Uncertainty in demand, transportation costs are considered and to counteract this uncertainty the robust optimization approach is used. The proposed supply chain network consists of four levels of forward supply chain and four levels of reverse chain. The proposed model is a mixed integer linear programming (MILP) model with the aim maximizing profit and minimizing generated pollution by transportation of products, and operational centers. The proposed model is solved by lingo software, so that the multi-objective model has been handled by utility based goal programming method. Finally, the results are analyzed and the comparison of different scenarios indicates that the objective function has strongly shown the uncertainty parameters and the effect of uncertainty in the parameters simultaneously. Therefore, network modeling based on different scenarios can be a good tool for deciding on confrontation with uncertain and ambiguous parameters.

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency for a set of Decision Making Units (DMUs) based on their inputs and outputs. There are weaknesses in conventional models DEA. Most important of which is the weight shift input and output which makes the efficiency of Decision Making Units with different weights measured. A characteristic of Traditional DEA models is that it allows DMUs to measure their maximum efficiency score with the most favorable weights. As well as the conventional DEA models are not focused network of evaluation units. In this paper we propose to correct the weaknesses the common set of weights (CSW) in network DEA model based on the Goal programming approach. To test the effectiveness of the proposed model and solve real data is used by insurance companies active in Qazvin province. The model presented in this paper units decide on a similar scale with a set of weights for neutral evaluation is common. Proposed approach helps policy makers to better understand the strengths and weaknesses of DMUs and try to promote the strengths and remove weaknesses to improve the efficiency and ranking of given DMUs.

design of two phrase mathematical model for green supply chain Green supply chain has attracted considerable attention of the governments and organizations over the past decades. The objective of this research is to suggest an integrated approach for green supply chain management including two stages. In the first stage, a TOPSIS-Fuzzy approach was presented to consider uncertainty in human’s judgment. In the second stage, we applied a robust Multi Objective Mixed-Integer linear Programming model to design the green supply chain network. Although many researches have been conducted on green supply chain management, most of them have not given enough importance to integrate decision making in supply chain. Moreover, most of former researches assume that supply chain is a balanced system. Also very few studies have considered carbon emission and the related issues in supplier evaluation which cause on overall warming and pollution of the planet. The model was designed for an active company in glass industry. results have revealed that the model is capable of controlling the network uncertainties.

The maximum capture problem seeks to find a suitable location for facilities in the network space and in a competitive condition. In this problem, the new company intends to enter the market with the aim of capturing more demand. In this study, the cost factor is considered to be a separate objective function and a bi-objective model is proposed. The number of facilities parameter is considered to be an interval and for its upper and lower bounds calculations two models are proposed. To obtain upper bound a model with the maximum capture objective and the maximum budget constraint and to obtain lower bound a model with the minimum cost objective and the minimum market share constraint. To solve the proposed model, a goal programming method is used. The steps of the research methodology and modelling are shown in a case study from Yazd city. The results show that if the weight of the objective functions is assumed to be equal and the investor neglect 7 % of the market share, 55% of initial investment could be saved.

One of the most important problems facing distribution companies is to find the best locations for depots and also proper routes for transportation vehicles in order to optimize their supply network. This study aims to examine the problem of location-routing for post offices in Tehran. To achieve this, a bi-objective location-routing problem is proposed. In order to make the problem more realistic, time constraints are taken into account. A suitable solution procedure on the basis of customized goal programming is developed to solve the proposed model. The proposed model and solution procedure are applied in post offices in Tehran, Iran. The results of proposed model show considerable savings in time and cost of planning in comparison with the current planning in the case. The proposed model can be applied in other cases such as location of garbage bins in city and routing of collecting vehicles. Other significant parameters in urban planning can be considered as uncertainty in this model in the future research. This model can be customized for whole of Iran and therefore, meta-heuristic methods can be used to solve the instances in large scale

Balance growth in economic, social and environmental dimensions, can ensure long-term success of any supply chain and considering these dimensions in designing and planning of supply chain is the cause of configuration of sustainable supply chain. On the other hand, integrity of financial and physical flow of supply chain plays a key role in success of supply chain to achieving its goals. Therefore, an integrated financial-physical planning model for closed-loop sustainable supply chain is proposed in this paper. Objectives of proposed model are maximizing profit, minimizing environmental and social effects and minimizing deviation of financial indicators from desired values. In order to cope with multi-objective nature of the problem, goal programming approach is implemented. Proposed model encompasses production, distribution and collection plan which is implemented in a real case in plastic recycling industry. Results of research prove effectiveness of considering financial indicators in master planning of sustainable closed-loop supply chain.