International Journal of Industrial Engineering & Production Research

---

The CPM (critical path method) technique is to search out the longest path to try and do activities, so as to compress and cut back the time it takes for a project, which finally ends up inside the creation of an identical and intensive network of activities inside the targeted work. This formal random simulation study has been recognized as a remedy for the shortcomings that are inherent to the classic critical path technique (CPM) project analysis. Considering the importance of time, the cost of activities within the network, and rising the calculation of the critical path during this study, Critical Path technique has been applied to improve critical routing intelligence. This study, by simulating and analyzing dragonfly's splotched and regular patterns, has obtained the precise algorithm of attainable paths with the smallest amount cost and time for every activity. This has been done to put down the restrictions and enhance the computing potency of classic CPM analysis. The simulation results of using Dragonfly Algorithm (DA) in CPM, show the longest path in shortest time with the lowest cost. This new answer to CPM network analysis can provide project management with a convenient tool.
 

---

Nowadays, Military products of superpowers countries have a high level of diversity, delivery speed, and appropriative operational functionality. Therefore, Production of varied, high quality and high speed delivery military products, is essential for enhance Iran's defensive deterrence power.
Defense industries supply chain agility is an answer to how to produce military products with these features. This paper, with the aim of providing supply chain agility model in defense industries, first, identifies the most important supply chain agility practices, Then, using factor analysis, categorizes the practices and validates them based on structural equation modeling (SEM) and finally, using Interpretative Structural Modeling (ISM), presents a model that shows the relationships and hierarchy between these practices. The results show that out of a total of 62 practices introduced in the previous research for agile supply chain, 41 practices in the agility of the supply chain of defense industries are effective. These practices were classified in 8 categories include supplier relationship, workshop level management, organizational structure improvement, human resource management, product designing, improve and integrate the process, application of information technology, and customer relationship. Improvement of organizational structure was at the lowest level of the model. Therefore, managers first should focus on it.
 

---

The frequency of chronic diseases such as cardiovascular diseases has significantly increased in recent years. This study is a developmental research which is categorized as descriptive-survey in terms of data collection method. The aim of this study is to prioritize 22 districts of Tehran for the purpose of prevention from cardiovascular diseases. In the present study, after extraction of the effective factors on the prevalence of cardiovascular diseases from previous studies, the weight of each factor with their specific data for each 22 districts of Tehran (collected from relevant organizations) is obtained using two levels of Fuzzy Delphi method and one level of fuzzy best-worst method, for confirming or denying factors and weighting them based on the opinion of 25 cardiologists, respectively, and transferred to Arc GIS software for prioritizing 22 districts of Tehran.Using a combination of fuzzy best-worst method, which is one of the newest methods for making multi-criteria decision, and GIS, for weighting parameters and prioritizing 22 districts of Tehran, gives an acceptable worth to the present study.Our results-after classification, drawing, and combination of maps- indicated that the 8^th district (except a little part in the west) is the best district, and 16^th and 19^th districts (approximately whole district) are in the last priority for prevention of cardiovascular diseases. Other districts respectively placed in the second to 21^th places.

---

CNC turning is widely used as a manufacturing process through which unwanted material is removed to get the high degree of surface rough. In this research article, Taguchi technique was coupled with grey relation analysis (GRA) to optimize the turning parameters for simultaneous improvement of productivity, average surface roughness (R_a), and root mean square roughness (R_q).Taguchi technique L27 (3⁴) orthogonal array was used in this experimental work. Feed, speed, and depth of cut were considered as the controllable process parameters. average roughness (R_a), root mean square roughness (R_q),and material removal rate (MRR) were considered as the performance characteristic and from TGRA result, it was revealed that the optimum combinational parameters for multi-performance, based on mean response values and confirmation experiments with Taguchi-based GRA is A1B1C1 (Vc=400 rpm, f=0.06 mm/rev, and DOC=0.5 mm). The optimum values obtained from experimental investigations for R_a was 6.86 μm, and MRR was 20690.31 mm³/s,further analysis of variance(ANOVA) were applied and it was identified that the depth of cut having most significant effect followed by speed and feed for multiresponse optimization. The percentage contribution of depth of cut was 38.28.71 %, speed was 11.89 % and feed was 8.466 %.
CNC turning is widely used as a manufacturing process through which unwanted material is removed to get a high degree of surface roughness. In this research article, Taguchi technique was coupled with grey relation analysis (GRA) to optimize the turning parameters for simultaneous improvement of productivity, the average surface roughness (R_a), and root means square roughness (R_q). Taguchi technique L27 (3⁴) orthogonal array was used in this experimental work. Feed, speed, and depth of cut were considered as the controllable process parameters. average roughness (R_a), root mean square roughness (R_q), and material removal rate (MRR) were considered as the performance characteristic and from TGRA result, it was revealed that the optimum combinational parameters for multi-performance, based on mean response values and confirmation experiments with Taguchi-based GRA is A1B1C1 (Vc=400 rpm, f=0.06 mm/rev, and DOC=0.5 mm). The optimum values obtained from experimental investigations for R_a was 6.86 μm, and MRR was 20690.31 mm³/s, further analysis of variance(ANOVA) were applied and it was identified that the depth of cut having most significant effect followed by speed and feed for multiresponse optimization. The percentage contribution of the depth of cut was 38.28.71 %, speed was 11.89 % and feed was 8.466 %.

---

 

---

The number of nonconforming items in a sample is monitored using the fraction defective known as the np-chart. The performance of the np-chart in Phase II depends on the accuracy of the estimated parameter in Phase I. Although taking large sample sizes ensures the accuracy of the estimated parameter, it can be impractical for attributes in some cases. Recently, the traditional c-chart and the np-chart with some adjustments have been studied to guarantee the in-control performance. Due to technology progresses, researchers have faced high-quality processes with a very low rate of nonconformity, for which traditional control charts are inadequate. To ameliorate such inaccuracy, this study develops a new method for designing the np-chart, such that the in-control performance is guaranteed with a pre-defined probability. The proposed method uses Cornish-Fisher expansions and the bootstrap method to guarantee the desired conditional in-control average run length. Through a simulation study, this study shows that the proposed adjustments improve the np-charts’ in-control performance.

---

Abstract
Background: In this paper healthcare condition of 31 countries that are the members of Organization for Economic and Co-operative Development (OECD) is measured by considering 14 indicators that are relevant to three main pillars of sustainable development.
Method: To estimate the efficiency scores, Principle Component Analysis-Data Envelopment Analysis PCA-DEA additive model in both forms of envelopment and multiplier is used to determine efficiency scores and also to define benchmarks and improvement plan for the inefficient countries. Then Decision Tree Analysis is also used to realize that which factors were the most influential ones to make a county an efficient Decision Making Unit (DMU).
Results: According to the PCA-DEA additive model, among 31 OECD countries, 16 countries have become inefficient, that USA have taken the lowest efficiency score, and among efficient countries Iceland could be considered as a paragon which has the highest frequency between the countries that are defined as the benchmarks. Decision tree analysis also show that exposure to PM2.5 is an influential factor on the efficiency status of countries.
Conclusion: This research gives an insight about the sustainable development and healthcare system and show the impressive effect of environmental and social factors like: exposure to PM2.5 and water quality, population insurance coverage, and AIDS on the healthcare efficiency of OECD countries

---

   This paper deals with a multi- objective linear fractional programming problem involving probabilistic parameters in the right- hand side of the constraints. These probabilistic parameters are randomly distributed with known means and variances through the use of Uniform and Exponential Distributions. After converting the probabilistic problem into an equivalent deterministic problem, a fuzzy programming approach is applied by defining a membership function. A linear membership function is being used for obtaining an optimal compromise solution. The stability set of the first kind without differentiability corresponding to the obtained optimal compromise solution is determined. A solution procedure for obtaining an optimal compromise solution and the stability set of the first kind is presented. Finally, a numerical example is given to clarify the practically and the efficiency of the study.
 

---

   This paper aims to study multi- objective assignment (NMOAS) problem with imprecise costs instead of its prices information. The NMOAS problem is considered by incorporating single valued trapezoidal neutrosophic numbers in the elements of cost matrices. After converting the NMOAS problem into the corresponding crisp multiobjective assignment (MOAS) problem based on the score function, an approach to find the most preferred neutrosophic solution is discussed. The approach is used through a weighting Tchebycheff problem which is applied by defining relative weights and ideal targets.  The advantage of this approach is more flexible than the standard multi- objective assignment problem, where it allows the decision maker (DM) to choose the targets he is willing. Finally, a numerical example is given to illustrate the utility, effectiveness and applicability of the approach.
 
  
 

---

It is indispensable that any manufacturing system is consistent with potential changes such as fluctuations in demand. The uncertainty also makes it more essential. Routing Flexibility (RF) is one of the necessities to any modern manufacturing system such as Flexible Manufacturing System (FMS). This paper suggests three mixed integer nonlinear programming models for the Unequal–Area Stochastic Dynamic Facility Layout Problems (UA–SDFLPs) by considering the Routing Flexibility. The models are proposed when the independent demands follow the random variable with the Poisson, Exponential, and Normal distributions. To validation of the proposed models, many small-sized test problems has solved that derived from a real case in literature. The large-sized test problems are solved by the Genetic Algorithm (GA) at a reasonable computational time. The obtained results indicate that the discussed models for the UA–SDFLPs are valid and the managers can take these models to the manufacturing floor to adapt to the potential changes in today's competitive market.
 

---

Sustainable supply chain networks have attracted considerable attention in recent years as a means of dealing with a broad range of environmental and social issues. This paper reports a multi-objective mixed-integer linear programming (MILP) model for use in the design of a sustainable closed loop supply chain network under uncertain conditions. The proposed model aims to minimize total cost, optimize environmental impacts of establishment of facilities, processing and transportation between each level as well as social impacts including customer satisfaction. Due to changes in business environment the uncertainty existed in the research problem, in this paper the chance constrained fuzzy programming approach applied to cope with uncertainties in parameter of the proposed model. Then the proposed multi-objective model solves as single-objective model using LP-metric method.

---

Todays, the variety of new products will raise the competition between manufacturers. Product portfolio management (PPM) as a suitable tool can influence the customer’s taste and increase the profit of firms. In this paper, the factors of PPM, production planning and a two-player continuous game theory are considered simultaneously. Some constraints are also assumed such as the availability of raw materials and the demand of each product based on some criteria. Two firms have same offered products and compete with each other. The relationships between two producers will be modeled by a non-zero two- player game. A numerical example is presented too. The proposed model is single period that the inventory is equal to zero in the start and finish of period. The objective functions show the profit of products and the constraints are included the utility of products for each customer, the market's share as a function of the probability of customer selection for each section, the type of distribution function for sale quantity, the accessible quantity of the sum of used materials by two producers and etc.
The results shows that demand changing effects on the profit of two players, but effects more on the second player. Also the sale price changing effects on the profit of two players, but effects more on the first player. The obtained data shows that if extra sale price increase the profit of first player will increase while the profit of second player is constant approximately.

---

The aim of the study is to develop theoretical and methodological foundations, scientific and practical recommendations for improving the management and evaluation of public debt in Ukraine. The methodological foundations of the study are a systematic approach to the analysis of the relationship of financial phenomena and processes, creative reflection on the works of Ukrainian and foreign scientists on public debt, and its role in the context of macro-financial stabilization. Specific scientific theoretical and applied developments by the applicant were obtained using the following methods: graphical financial analysis (for studying the tendencies of debt formation); statistical-economic (to identify the impact of public debt on socio-economic processes); economic-mathematical modeling (to determine the relationship between public debt and macroeconomic indicators). On the basis of the research, it was revealed that the selected macroeconomic indicators have a significant impact on the government debt, and there are difficulties in coordinating international, regional economic integration or creating a broad separation based on stable international competitiveness. In order to test the impact of some macroeconomic indicators on the size of public debt, the World Bank's economic indicators have been taken as the main material for research. The analyzed period of time is 2001-2017 years.
The recommendations provided in this article will contribute to the development of public debt management and the associated increase in the living standards of the country's population. Based on the analysis conducted, there are every reason to assert that effective management of public debt can contribute to the development of the national economy. The scientific novelty of the study is to determine the impact of some macroeconomic indicators on public debt management at the current stage of Ukraine's development.

---

In the era of digitization and globalization, national higher education systems face a number of challenges of the exogenous nature. Intensification of the competition in the educational services market necessitates the search for new ways of increasing the level of the competitiveness of universities and higher education systems as a whole. Development of theoretical, methodological and applied foundations of the formation and implementation of the integrated model of the competitive higher education becomes relevant. Application of the interdisciplinary approach to the research allows combining tools and techniques of different sciences. Economic, psycho-pedagogical, legal and managerial blocks are structural components of the proposed model of the competitive higher education. The effective implementation of such a model requires the involvement of a wide range of stakeholders and the impact of changing factors in the exogenous environment. Successful implementation of the model requires the existence of a developed regulatory framework harmonized with the provisions of the EU legislation. Practical implementation of the model concept proposed in this article will increase the competitiveness of the national higher education system in a highly competitive global scientific and educational area.

---

The article examines foreign and domestic experience in organizing financial monitoring systems, systematizes the requirements for its implementation in Ukraine. The basic legal norms, enshrined in the joint directives of the European Parliament and of the Council of the EU, and underlying the national financial monitoring systems of the EU countries and Ukraine have been also analyzed. Taking into account the fact that the risk-based approach is the main basis for the effective implementation of all FATF recommendations, the nature of the risk of money laundering / financing of terrorism and the criteria for their assessment have been investigated. A scheme of improving the process of financial monitoring in a bank has been developed, as well as a number of measures have been proposed to raise the level of adhering to the legislation in the field of anti-money laundering and counter-terrorist financing by the banking sector.

---

The processes of transformation of the energy space, namely the impact of alternative energy resources on it, are characterized by changes in the national economy in general and in the energy market in particular. The results of the analysis confirmed the significant dependence of electricity production indicators on renewable sources and such factors as GDP, CO₂ emissions, total electricity production, which requires improvement of organizational and economic bases for policy development of state support for renewable energy technologies in countries with exogenous factors. The interdependence between electricity production from renewable sources and economic indicators in Ukrainian-Chilean relations using macroeconomic multifactor analysis based on the correlation method allowed to identify the most influential factors.

---

In the last few decades, profile monitoring in univariate and multivariate environment has drawn a considerable attention in the area of statistical process control. In multivariate profile monitoring, it is required to relate more than one response variable to one or more explanatory variables. In this paper, the multivariate multiple linear profile monitoring problem is addressed under the assumption of existing autocorrelation among observations. Multivariate linear mixed model (MLMM) is proposed to account for the autocorrelation between profiles. Then two control charts in addition to a combined method are applied to monitor the profiles in phase II. Finally, the performance of the presented method is assessed in terms of average run length (ARL). The simulation results demonstrate that the proposed control charts have appropriate performance in signaling out-of-control conditions.
 

---

Data envelopment analysis (DEA) measures the relative efficiency of decision-making units (DMU) with multiple inputs and multiple outputs. In the case of considering a working team as a DMU, it often comprises multiple positions with several employees. However, there is no method to measure the efficiency of employees individually taking account the effect of teammates. This paper presents a model to measure the efficiency of employees in a way that they are fairly evaluated regarding their teammates’ relative performances. Moreover, the learning expectations and the effect of learning lost due to operation breaks are incorporated into the DEA model. This model is thus able to rank the employees working in each position that can then be utilized within award systems. The capabilities of the proposed model are then explored by a case study of 20 wells with 160 distinct operations in the South Pars gas field, which is the first application of DEA in the oil and gas wells drilling performance analysis.
 

---

One of the basic assumptions of classical production-inventory models is that all products are of perfect quality. However, in real manufacturing situations, the production of defective items is inevitable, and a fraction of the items produced may be naturally imperfect. In fact, items may be damaged due to production and/or transportation conditions in the manufacturing process. On the other hand, some reworkable items exist among imperfect items that can be made perfect by additional processing. In addition, the classical production-inventory models assume that there is only one product in the system and that there is an unlimited amount of resources. However, in many practical situations, several products are produced and there are some constraints related to various factors such as machine capacity, storage space, available budget, number of allowable setups, etc. Therefore, we propose new constrained production-inventory models for multiple products where the manufacturing process is defective and produces a fraction of imperfect items. A percentage of defective items can be reworked, and these products go through the rework process to become perfect and return to the consumption cycle. The goal is to determine economic production quantities to minimize the total cost of the system. The analytical solutions are each derived separately by Lagrangian relaxation method, and a numerical example is presented to illustrate and discuss the procedure. A sensitivity analysis is performed to investigate how the variation in the inputs of the models affects the total cost of the inventory system. Finally, some research directions for future works are discussed.

---

The present study is focused to investigate the effect of the various machining input parameters such as cutting speed (v_c), feed rate (f), depth of cut, and nose radius (r) on output i.e. surface roughness (R_a and R_q) and metal removal rate (MRR) of the C40 steel by application of an artificial neural network (ANN) method.  ANN is a soft computing tool, widely used to predict, optimize the process parameters. In the ANN tool, with the help of MATLAB, the training of the neural networks has been done to gain the optimum solution. A model was established between the computer numerical control (CNC) turning parameters and experimentally obtained data using ANN and it was observed from the result that the predicted data and measured data are moderately closer, which reveals that the developed model can be successfully applied to predict the surface roughness and material removal rate (MRR) in the turning operation of a C40 steel bar and it was also observed that lower the value of surface roughness (R_a and R_q) is achieved at the cutting speed of 800 rpm with a feed rate of 0.1 mm/rev, a depth of cut of 2 mm and a nose radius of 0.4 mm.