فصلنامه مطالعات مدیریت صنعتی
پیاپی 58 (پاییز 1399)

This paper investigates a joint economic lot sizing model for a two echelon supply chain consisting of a single-vendor and multiple buyers. Recent studies have focused on the problem assuming equal batch sizes for each retailer and analytical models have been proposed. Based on hill’s study on unequal batch sizes which improves the performance of the model, the purpose of this study is to proposes a mixed integer nonlinear programing model considering unequal batch sizes while shortage is permitted and a boundary constraint on the backorder at the retailer is imposed. The objective function consists of supplier’s set up cost, holding cost, fixed shipment cost and retailer’s ordering cost, holding cost and shortage cost. An optimal solution is obtained and the results show that releasing the assumption of equal batch sizes delivers a more cost efficient solution. A sensitivity analysis is then conducted to explore the effect of changing parameters on the solution.

In general, numerous studies have paid a special attention to machine planning,job allocating andjob sequencing in scheduling problems to optimize makespan. Due to the relation among economy, energy and environmental concerns, energy use is one of the most important issues in different systems planning. In this paper, a scheduling of heterogeneous parallel machines is studied, in which the job process speed on every machine is settable. Since there is a direct link between used energy of machines and process speed, the purpose of the paper is to minimize total used energy and tardiness-related costs in delivering customers' demand. In order to optimizing the problem, two meta-heuristic algorithms, Memetic algorithm and Genetic algorithm, are developed, finally the results of both algorithms are analyzed and then compared to each other as well as to the results of the GAMS optimization software. Keyword: heterogeneous parallel machines scheduling, total lateness costs, Energy costs. Memetic algorithm

Today, it is difficult for organizations to survive without improving supplier performance and supplier relationships or gain competitive advantage. Therefore, suppliers must be managed and developed to meet the needs of the producer company. On the other hand, the supplier's development requires the introduction of precise and comprehensive criteria. The purpose of this paper is to identify the dimensions and categories of supplier development based on the criteria related to it, using the Meta-synthesis method. For this purpose, by first selecting 102 studies from 136 studies, coding their texts with Atlas TI software, 23 concepts were identified for the criteria. Subsequently, through the analysis of literature and the output of VOSviewer software, the identified concepts were classified into four tangible, intangible, environmental, and external dimensions and internal dimensions. To verify validity, triangulation of data sources and researcher has been used. The content validity ratio and content validity index were calculated by a survey of automobile industry experts, four of the criteria were directly eliminated, and modifications and modifications were made on the criteria, and finally, 17 criteria for the development of suppliers in the automotive industry were finalized. The amount of Kappa coefficient obtained shows the reliability of the identified criteria. In the end, a two-dimensional model is proposed for the supplier-development criteria. Due to the lack of categorization of the criteria related to the supplier's development in previous studies, and in particular in domestic research, the identified criteria and their categorization can be useful for researchers in this field.

Locational decisions, routing and allocation in supply chain management philosophy is undoubtedly one of the most important issues that affect the frequency of the supply chain cost reduction and customer satisfaction. This paper presents an integrated approach to the distribution network. The objective function of the proposed mathematical model consists of minimizing the total costs associated with transportation and warehouse rental costs and also minimize the risk of system. The model has high computational complexity and the exact method of solving it is not possible in a reasonable time. The result is an innovative multi-objective algorithm known as the objective harmony search algorithm is presented. To demonstrate the effectiveness and efficiency of the proposed algorithm to solve the model using the Taguchi method algorithm parameters are adjusted in the best possible rates. Then a random sample of the issues and the performance of the proposed algorithm with NSGA-ǁ and NRGA evaluated.

Green building has attracted widespread attention in recent years. Increasing building projects in Iran has had significant environmental impacts and green building implementation is an appropriate approach to reduce the environmental risks. Green building projects are unwittingly exposed to risks that reduce their efficiency, Therefore, identifying and ranking the risk can play a significant role in the success of green building projects. Due to the few studies in this area in Iran, This study aims to provide a new comprehensive framework of all the criteria and risks of green building projects. For this purpose, the first step aims to identify and to screen the risks from the viewpoint of experts in green building projects and introduction of risk assessment criteria. After that, the next step is to apply the SWARA method to obtain the weight of the criteria. Finally, Ranking of the risks of green building projects which is taking into account the results of the initial steps, has been done using the COPRAS method. This is the first attempt to solve a green building project by using a hybrid of SWARA and COPRAS through a case study (Amol). The results show that risks of: the low quality of materials and equipment, the stakeholder resistance to approve the green ideas and lack of realistic goals are very important. The proposed framework can help stakeholders of green building projects in developing countries to manage project risks more efficiently.

Data Envelopment Analysis (DEA) is an estimator. This estimator tries to assess a relationship between multiple inputs and multiple outputs, and an identified technology. In traditional DEA models, firms are classified into two divisions, efficient and inefficient. Efficient firms are considered as a reference for inefficient firms. In traditional DEA models, the efficiency improvement has been inspected for inefficient firms and efficient firms are assumed to be unchanged. Since the estimated technology is rationally smaller than the real technology or in other words, the estimated technology is always the subset of the true technology, we can expand it a little. Thus, we can improve efficient firms. This is done by creating some virtual DMUs. In this paper, an algorithm is proposed to expand the Production Possibility Set (PPS) and to improve efficient firms. To illustrate the proposed approach, numerical and applied examples are provided. The results are explained and discussed.

This paper proposes a bi-objective model for the waste collection problem and considers the location, routing and inventory of the system simultaneously. Considering the reverse flow of the system is another feature of the current study. In the proposed model, the total costs of the system are minimized. In addition, the related risks of opening new centers and transportaion are included as the second objective function of the problem. Considering the delivery time and cpacity of vehicels constraints, are the other features of the model. Due to the NP-hardness of the model, two metaheuristic algorithms namely a non dominated sort ordering genetic algorithm (NSGA-II) and a multi objective particle swarm optimization algorithm (MOPSO) are applied to solve the problem. According to the results, NSGA-II is able to reach better answers in all the propsed metrics. According to sesitivity analysis, foreign transportation fleets make a great impact on the costs of the system.

The study aims to simulate the strategies of Islamic Azad University, Tabriz branch during 2019- 2034 period through system dynamics approach. Based on research literature, the variables of student trend, physical resources, educational quality, human resources, research and publication and financial operation were considered as key effective variables in formulating the mentioned strategies. The interaction between variables i.e, the dynamic hypothesis is demonstrated by causal-loop diagrams and state-current maps. Then, the causal relations were defined in the form of mathematical functions and finally simulated by using reliable theories in the field of problem-solving literature and experts' opinion. The scenarios were formulated and analyzed based on three main objects, namely cost reduction, increase of revenue and educational quality development. Our results showed that by the implementation of downsizing scenario in Tabriz Azad university, the tuition rate of the university experienced a decrease of five percent. The second scenario showed that if research budget experiences a change of 40%, non-fee revenues would grow 19%. The simulation of the third scenario revealed that, 25% increment of new investments in Tabriz Azad University leads to the growth of student attraction rate by 17% in long term. Taking the results of three scenarios into consideration makes us to suggest that it is advisable that Tabriz Azad University should follow the two strategies of increasing research budget and making use of new investments.

Nowadays, managers in the public and private sectors consider having knowledge of green laws and issues as essential to the survival of their organizations. Although today researchers have promoted each issue of green human resource management and green supply chain management separately, but there has been a great deal of delay in integrating these two issues. Therefore, this study first attempts to provide an integrated and coherent framework for linking green human resource management and green supply chain management (GHRM-GSCM). For this purpose, firstly, using a comprehensive literature review of the research, interviews and expert opinion on the ornamental industry, the initial identification of evaluation indicators in green supply chain management and green human resources management was undertaken. In the next step, were determined the causal relations by using the fuzzy DEMATEL method and the fuzzy ANP method with the weight of each of the criteria and sub-criteria. The results of this assessment show that the factors of leadership, flexibility, and environmental importance are identified as effective factors, and optimizing these factors by the Arya array industry can caused to the optimization of other factors (influencing factors).

This paper deals with the problem of two-stage assembly flow shop scheduling with considering sequence-independent setup times. The objective is to minimize total completion times of all orders. In this problem, there are several orders for one type of product. Each ordered product is formed of several different parts. At first, the parts are manufactured in a flow shop stage with some different machines and then they are assembled into a final product on a single machine. This paper presents three meta-heuristic algorithms, namely Parallel Variable Neighborhood Search (PVNS), Artificial Immune Algorithm (AIA) and Simulated Annealing (SA), for solving under studied problem. The Taguchi experimental design method as an optimization technique is employed to tune different parameters and operators of presented algorithms. Also, Numerical experiments are used to evaluate the performance of the proposed algorithms. The results show that the PVNS algorithm performs better than the other algorithms.