مجله مدیریت تولید و عملیات
سال نهم شماره 1 (پیاپی 16، بهار و تابستان 1397)

This paper aims to examine the scheduling of vehicles in a multi-product supply chain regarding to the mutual relationship between the transportation and the manufacturing units. The integration level in the supply chain consists of a manufacturer and its first tier suppliers, which are linked by a transportation fleet. The problem is determining orders allocation to the suppliers, orders production sequence at the suppliers, orders allocation to the vehicles, and orders transportation priority, in order to minimize the sum of orders delivery time. This issue has not been discussed in the literature, so far. At first, the mathematical model of the problem is presented, then the NP-Hardness of the problem is demonstrated. For solving the problem, a new combination of genetic algorithm and simulated annealing algorithm, named as Populated Simulated Annealing algorithm (PSA) is proposed. For verifying the PSA, its results are compared to results of simulated annealing algorithm (SA) and developed version of DGA algorithm, proposed for the nearest problem in the literature to our problem. Furthermore, relaxing some hypothesis, the results of PSA are compared to DGA results. All of the comparisons show that PSA is more efficient than the other algorithms. Finally, comparison of PSA with exact solution for small size problems demonstrates its proper efficiency.

Supply Chain Management (SCM) is considered a strategic factor for the better attainment of organizational goals such as enhanced competitiveness, improved product quality and increased profitability in cement industry. This research aims at competitive positioning of LARG supply chain in Iranian cement industry and its strategic requirements (Strenghts, Weaknesses, Oportunities and Threats) Importance-Performance Analysis (IPA). A survey-descriptive research method was applied and an available sample which includes 11 Iranian cement companies were selected. First, using literature review and Delphi Method (DM), strategic requirements of LARG supply chain in the cement industry were identified. In the next step, the importance of strategic requirements was determined using SWARA method. Then, the results of applying Internal/External Factors Evaluation (IFE/EFE) matrix showed that the suitable position for LARG supply chain in Iranian cement industry would be an aggressive strategy. In the final step, applying Importance-Performance Analysis (IPA) matrix showed all requirements for the aggressive strategy, except exporting opportunities and cooperation culture in supply chain, were evaluated in quadrant II (keep up the good work). Finally some suggestions are presented toward improving LARG supply chain performance in Iranian cement industry.

Facility Layout Problem (FLP) is an important issue in plant design, which directly affects production costs as well as safety concerns. Hierarchical and integrated approaches are two main methods used for the formulation of FLP. In the hierarchical approach, FLP is solved after the completion of the process design and scheduling, while the integrated approach treats FLP simultaneously with other phases. This paper presents a new approach based on the candidate groups for interactive functions; incorporating the advantages of the previous approaches.
In the new approach, the design phases prior to FLP results in a set of models introducing by the engineering team in advance. Next, the models are solved such that instead of individual designs, a set of suggested structures are generated. These structures are then fed into the FLP as input data and solved by mixed integer programming technique. Some characteristics of the models are: presence of the hub stations, different and variable dimensions for each station, possibility of rotation for the stations and incorporating safety distances. Finally, test problems are solved and results are discussed. It should be noted that if a candidate group entails a different production flow then a different optimum solution might be obtained.

This paper proposes a decision support system for the evaluation and prioritization of imports in sanction atmosphere based on fuzzy quantitative models which are implemented in an Iranian pharmaceutical company. The most important risks are obtained include international payment restrictions and shipping risks. At the end, the strategies are presented to alleviate the spotted risks. Today’s organizations are facing many different risks, especially the ones whose nature of work is mostly commercial and are engaged in importing goods. Therefore, in order to survive and to reduce the activity risks, these organizations should constantly be under review and monitoring.
In addition to common risks in the process of importing goods, the tough sanctions against some countries like Iran, have caused the importing of goods to become one of the most risky work. For this reason, in order to prevent the expanding problems arising from sanctions, it is necessary to determine the importance and priorities of the risks along with recognizing their occurrences on time. Thus, by analyzing and prioritizing the risks, it is possible to distribute the rare resources of the organizations effectively.
With the presence of the sanctions, many decisions related to the imports are vague and uncertain; while making decision in the shortest possible time in these cases is a vital matter. These facts indicate the importance and the necessity of having a system to support the decisions on evaluating and prioritizing of risks in importing goods. Therefore, in this paper, a decision support system has been designed and implemented to evaluate and prioritize the risks involved in importing goods in Isfahan Farabi Pharmacy Company as a case study. A few models in decision support system are able to manage the available data even if they are vague and uncertain.

İn this research, with inspiration from Project Management Body of Knowledge (PMBOK) model which is one of the most comprehensive models in risk management, a new model is presented to analyze and prioritize the risks of importing goods at the time of imposing sanctions. This model consists of five stages: 1- planning for analysis and priority of the risks, 2- identifying these risks, 3- analyzing the risks which means to review and evaluate four criteria of ‘the possibility of the occurance of the risks’, ‘the degree of the effect of the risks’, ‘organizations’ ability in response to these risks’ (McDermott and colleagues, 2009), and ‘the uncertainty of decision makers in estimation’ (Klein & Cork, 1998). Thus, GFAHP and VIKOR methods by phase, group, and Grey Relationship Analysis for risk prioritizing will combine together; 4- planning in response to the risks; 5- controling and following up of risks.
Implimentation of the suggested model for a case study (Farabi Pharmacy Company) is performed as follows: The system designed consists of three segments: 1- Data Base: the data based on this system is prepared by using Microsoft Excel software. 2- Original Model: this is the main section of the system which provides the possibility of performing calculations and MatLab software has been used for coding purposes. 3- User Interface: this will provide the communication between the user (decision makers) and the system.

The presented model was used to manage the risk of importing goods by using a software system which is designed in Farabi Pharmacy Company and the most important risks related to importing pharmaceutical ingredients in this company are recognized to be as follows: 1- risks related to transportation of importing goods, 2- unsecured paths of transfering exchanges, 3- failure to timely payment of exchange to selling companies, 4- the purchase from available limited and invalid suppliers, 5- lack of training and previous commercial experiences in confrontation with sanction situations, 6- increase of the values of foreign exchanges as compared with Iranian Rial, 7- liquidity shortage at sanction situation, 8- putting the commercial performance related to supply chain under pressure, 9- the decrease in precise and correct information in supply chain, 10- to decrease product quality as a result of bottlenecks arising from sanctions.
After performing stages of analysis of risks by decision support system, the risks of ‘failure to timely payment of exchange to selling companies’, ‘unsecured paths of transfering exchanges’, and risks related to ‘transportation of importing goods’ were found to have the highest priorities. Therefore, the organization resources should first be used to edit and execute the strategies for management of these risks.

This paper has paid attention to quantifying the risks of importing goods for the first time and has presented a combined method of quantity models in decision making for offices. Using such a system in importing goods causes the recognition and control of related risks and the reduction of time and expences which are sometimes irreparable. The organization should spend most of its financial and human resources on executing a strategy for confrontation with risks of high priorities. At the end, some strategies for control and confrontation with each well known risks are presented.

In this paper, a new robust method based on weighted maximum likelihood estimation (WMLE) is proposed to estimate the regression parameters in logistic profiles in Phase I. This approach reduces the outlier’s effects on the statistical performance of T2 control chart in terms of probability of Type I error. A numerical example is used to evaluate the performance of the proposed method. The results show the better performance of the proposed estimator compared to the maximum likelihood estimation method in terms of power in T2 control chart.

In today's complex world when we talk about IT projects, risk appears such as an inseparable part. The purpose of this study is to identify risks in IT project management and their effect on the overall risk of the project. In order to achieve this objective, we study a wide range of researches in the field of IT project risk analysis. We classify risk factors and the factors are simulated in a dynamic model. Then, some equations are extracted using examining relationship between structures and factors, and the risks are studied in a period of 12 month. The results of this study show that human resource risk is the most important risk that is repeated, after that project management risk is the second risk. Strategic risk is a risk that is appeared in some periods. So, we suggest IT project managers to pay more attention to these risks in the politics and strategies.

The results of dynamic efficiency evaluation not only help managers to realize their business' position in competitive market, but also enable them to compare current company’s performance with previous periods and do strategic planning properly. For doing so, network data envelopment analysis is a logical approach. Hence, the main objective of this illustration is to measure dynamic efficiency by means of network data envelopment analysis technique. Although different approaches in network DEA are introduced recently, the need for a comprehensive methodology in this area is remained because of the defects of previous methodologies. Consequently, a novel approach based on multi-objective optimization is introduced in this paper in order to measure the efficiency of a network structure. Finally, the case of Machine Made Carpet Industry (MMCI) is used and the dynamic performance of MMCI's companies in the period of four years is measured. Efficiency results of case data showed that the methodology proposed in this paper is able to eliminate defects of previous approaches and evaluate both total and annual efficiency simultaneously

Packing is one of the well-known problems in operation research, especially in production planning. The main objective of studying the packing problem is to reduce the wastes of cutting through optimization of packing of pieces. Packing is a kind of NP-hard problem that the precise methods are not able to solve it. In this paper, in order to achieve an optimal packing of Non-guillotine cutting problems, the meta-heuristic emerging Imperialist Competitive Algorithm was used and the results were compared with the output of the genetic algorithm, which is the typical algorithm in solving packing problems. To achieve better solutions, the parameters of all meta-heuristics were calibrated with Taguchi experiment method. The efficacy of the proposed approach was tested on a set of instances, taken from the literature, and the results of the proposed algorithm were tested statistically by ANOVA. The results of this study showed that the meta-heuristic emerging Imperialist Competitive algorithm is more efficient and faster in solving packing problems.

The withdrawal Kanban system, by capability of data transferring in supply chain reduces different types of the waists such as inventories level and unnecessary movements. To achieve the aims of lean production, the parameters of the Kanban system such as the number of Kanban should be determined properly. The number of Kanban problem is a multi-objective problem which should met the aims of producers and suppliers simultaneously. In this paper, the objectives and constraints of withdrawal Kanban problem has been determined based on a case study in automobile supply chain. A mathematical integer multi-objective model with non-linear objects has been developed. Two sets of solutions are generated by the optimization model. A simulation model is developed to check the possibility and validity of solutions. The simulation studies show that one of the solutions can reduce up to 46 percent the inventory costs while increase 11 percent transportation costs compared to the current state.

In this paper, a multi-objective, multi-period and multi-product mixed integer programming model ‎for the supplier selection and quota allocation problem under an all-unit quantity discount policy, ‎constrained storage space and stochastic demand is considered. Also, due to the stochastic status of ‎the demand, we use the Chance Constrained Programming (CCP) in order to transform the inventory ‎balance equation to a stochastic position. Since the discount policy encourages the buyer to buy more while the storage capacity restricts, we require to consider both in the supplier selection and quota allocation problem; furthermore, different priorities for the objectives should be considered. We use the LP-metric method, goal programming and the novel solution technique ‎called multi-choice goal programming in order to model the multi-objective problem. Furthermore, a numerical ‎example using three modeling approaches, considering the different scenarios are solved. The differences ‎in the scenarios are the importance of the objective function in terms of the decision maker. Results ‎show if an objective function is prioritized, that objective will be closer to its optimal value.