International Journal of Industrial Engineering & Production Research

---

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.

---

To demonstrate the importance of customer satisfaction can mention numbers of the service providers that attempt to differentiate themselves by satisfied their customers, witnessed high growth. In this paper, some factors that increase retailers and customers’ satisfaction, such as driver consistent services and delivering fresh products, are considered in a perishable inventory routing problem (PIRP) under possibility and necessity class of fuzzy uncertainty measures. In a typical inventory routing problem (IRP), a distribution center delivers products to a set of customers through a limited time horizon, and simultaneously makes a decision about inventory and routing to minimize the total cost. The proposed model is formulated as mixed-integer programming. Two types of consistent driver services are regarded for different kinds of customers, including particular and typical customers. To investigate the validity of the model, the problem is solved for two values of possibility and necessity measures.
 

---

Laser marking is an advanced technology in material processing that has a permanent effect on materials. With the use of laser engraving, the material is removed, layer by layer, in the laser path through melting displacement, ablation, and evaporation. Al-SiC is a metal matrix composite, widely used in aerospace, automobile manufacturing, and electronic packaging. Accumulative roll bonding (ARB) is one of the newest manufacturing processes of metal matrix composites, which leads to the production of materials with high strength, low weight, and great environmental compatibility. In this paper, we present the laser engraving of Al-SiC composite samples, which are produced through ARB process, using Q-switched Nd:YAG laser. A 2^k factorial design is used to analyze the effect of factors, including assistant gas flow, distance of sample from beam focus location (distance), pulse repetition frequency, and pumping current on the qualitative characteristics of engraved zone (width, depth and contrast of engraved zone). Desirability function is used for optimization. Results based on experimental data indicate the optimal setting of input factors which leads to pre-specified target values of responses.
 

---

Today due to the globalization and competitive conditions of the market, decisions are generally made in group and in accordance with different attributes. In addition, all of the information is associated with uncertainty. In such situation, the emergence of inconsistency and facing with the contradictions will be obvious. Having regarded this fact, the development and application of tools that adequately address the uncertainty in decision making process and also be appropriate for group decision making is an important area of multi-criteria decision making (MCDM). Therefore, in this paper, firstly we developed the traditional best-worst method (BWM) and proposed an interval-valued intuitionistic fuzzy best-worst method (IVIFBWM), then introduced a novel approach for fuzzy multi-attribute group decision making based on the proposed method. Finally, in order to demonstrate how the introduced approach can be applied in practice, it is implemented in an Iranian investment company and the experimental results are examined. From the experimental results, we can extract that not only the introduced approach is simple in calculation but also it is convenient in implementation especially in interval-valued intuitionistic fuzzy environments.

---

In this study, the electrochemical machining (ECM) of the 304 stainless steel with the response surface methodology (RSM) approach for designing, analyzing and mathematical modeling was used. The electrolyte type, concentration and current parameters were considered as the machining parameters. The mathematical model for the responses was presented and based on the type of electrolyte including NaCl, NaNO₃ and KCl. The results showed that the current has the highest effect on Surface Roughness (SR) and Material Removal Rates (MRR) and respectively it improves them to 0.465μm and 0.425gr/min. The electrolyte concentration has the highest effect on Over Cut (OC) and causes to increase its values. Under the conditions of NaCl electrolyte, 1 molarity concentration and 55 A current, the optimum condition 0.4006 gr/min MRR, 0.75 mm OC and 0.465mm SR was achieved. 

---

In today’s world, manufacturing companies are required to integrate their sources with manufacturing systems and use novel technologies in order to survive in the competitive world market. In this context, computer integrated manufacturing (CIM) and its related technologies are taken as novel and efficient schemes; therefore, selecting the best technology among them has been a challenging issue. Such an investment decision is, in nature, a multi-attribute problem. In fact, manufacturing technologies have various advantages and disadvantages which need to be considered in order to choose the best one. In this paper, we briefly study the structure and goals of computer integrated manufacturing systems, the role of different sectors in traditional and modern manufacturing systems, and the effect of information communication on them. Then, various options regarding the implementation of an integrated computer manufacturing technology are introduced and a  combined model of the fuzzy analytical hierarchy process and fuzzy TOPSIS is proposed to handle the above-mentioned multiple criteria decision making problem. Finally, the considered options for manufacturing technologies are ranked using a numerical example.
 

---

Statistical monitoring of dynamic networks is a major topic of interest in complex social systems. Many researches have been conducted on modeling and monitoring dynamic social networks. This article proposes a new methodology for modeling and monitoring dynamic social networks for quick detection of temporal anomalies in network structures using latent variables. The key idea behind our proposed methodology is to determine the importance of latent variables in creating edges between nodes as well as observed covariates. First, latent space model (LSM) is used to model dynamic networks. Vector of parameters in LSM model are monitored through multivariate control charts in order to detect changes in different network sizes. Experiments on simulated social network monitoring demonstrate that our surveillance monitoring strategy can effectively detect abrupt changes between actors in dynamic networks using latent variables.

---

The blood supply chain network is an especial case of the general supply chain network, which starts with the blood donating and ends with patients. Disasters such as earthquakes, floods, storms, and accidents usually event suddenly. Therefore, designing an efficient network for the blood supply chain network at emergencies is one of the most important challenging decisions for related managers. This paper aims to introduce a new blood supply chain network in disasters using the hub location approach. After introducing the last studies in blood supply chain and hub location separately, a new mixed-integer linear programming model based on hub location is presented for intercity transportation. Due to the complexity of this problem, two new methods are developed based on Particle Swarm Optimization and Differential Evolution algorithms to solve practical-sized problems. Real data related to a case study is used to test the developed mathematical model and to investigate the performance of the proposed algorithms. The result approves the accuracy of the new mathematical model and also the good performance of the proposed algorithms in solving the considered problem in real-sized dimensions. The proposed model is applicable considering new variables and operational constraints to more compatibility with reality. However, we considered the maximum possible demand for blood products in the proposed approach and so, lack of investigation of uncertainty conditions in key parameters is one of the most important limitations of this research.

---

One of the most important fields of logistic network is transportation network design that has an important effect on strategic decisions in supply chain management. It has recently attracted the attention of many researchers. In this paper, a multi-stage and multi-product logistic network design is considered.
This paper presents a hybrid approach based on simulation and optimization (Simulation based optimization), the model is formulated and presented in three stages.  At first, the practical production capacity of each product is calculated using the Overall Equipment Effectiveness (OEE) index, in the second stage, the optimization of loading schedules is simulated. The layout of the loading equipment, the number of equipment per line, the time of each step of the loading process, the resources used by each equipment were simulated, and the output of the model determines the maximum number of loaded vehicles in each period. Finally, a multi-objective model is presented to optimize the transportation time and cost of products. A mixed integer nonlinear programming (MINLP) model is formulated in such a way as to minimize transportation costs and maximize the use of time on the planning horizon. We have used Arena simulation software to solve the second stage of the problem, the results of which will be explained. It is also used GAMS software to solve the final stage of the model and optimize the transporting cost and find the optimal solutions. Several test problems were generated and it showed that the proposed algorithm could find good solutions in reasonable time spans.

---

The subjects of reliability acceptance sampling plans and failure-censored life tests have usually been investigated from the viewpoint of statistical properties; indeed, few researchers have shed light on the economic aspects of these issues. In this research, a constrained mathematical model is developed to optimally design a reliability sampling plan under failure censoring life testing. Minimizing the expected total cost (ETC) involved in the sampling and life testing is considered as the objective function of the model. Ensuring the producer’s and the consumer’s risks is taken into consideration as the constraint of the model. To minimize the ETC, the model optimally determines three decision variables including the total number of the items put to the life test, the number of the failed items to terminate the test, and a criterion to make decisions about the acceptance or rejection of the lot. Examples are provided and analyses are conducted to gain some insight regarding the model performance. 

---

Sustainability is now increasingly recognized as an effective strategy to deal with the current challenges of global supply chains. Supply chains of the lead and zinc industries are most important. Because these two industries not only are among the high-risk in different countries, including Iran, but also can affect economic, social, and environmental sustainability. On the other hand, identifying and assessing the critical risks of supply chains have been less addressed in recent studies. This study aimed to identify and assess critical risks of sustainable supply chains (SSCs) in the Iranian lead and zinc industry. This study was a mixed-method (qualitative and quantitative) descriptive survey. Based on the literature, 24 risk factors that affect supply chain sustainability were identified, out of which 20 critical risk factors were confirmed in two steps by reviewing experts’ comments and the data obtained from in-depth interviews and questionnaires. The validity of questionnaires is verified based on the opinions of a group of 5 experts in the first step and another group of 17 experts and professionals of the lead and zinc industry in the second. The Cronbach’s alpha coefficient of the questionnaires was calculated to be 0.837, indicating the reliability of the questionnaires. The risk factors were analyzed using the Risk Priority Number (RPN), fuzzy DEMATEL, and risk matrices. Based on the results, “lack of technological/knowledge sustainability”, “price and cost fluctuations”, “inflation and exchange rates” and “environmental pollution” were the most important risk factors in the supply chain of the Iranian lead and zinc industry.

---

Productivity growth and efficiency improvements are the major sources of economic development. Pure efficiency, scale efficiency, and technology are basic factors, and rules and regulations and balance are recently known factors affecting the Malmquist productivity index. In this paper, we focus on the role of physical space facilities of bank branches as a factor affecting the decomposition of Malmquist productivity index. First, we propose a new model applying weight restrictions in basic DEA models for constant returns to scale technologies. The weight restrictions increase the discrimination power of basic DEA models. Then the new model is used to develop an extended Malmquist index, which gives a novel decomposition describing the roll of bank branch facilities on productivity growth or decline. The validity of proposed method is confirmed with a real data of 74 commercial bank branches in two time periods 2017 and 2018 and the results for both traditional and extended Malmquist index are analyzed.

---

In recent years, it has been proven that integrating statistical process control, maintenance policy, and production can bring more benefits for the entire production systems. In the literature of triple-concept integrated models, it has generally been assumed that the observations are independent. However, the existence of correlated structures in some practical applications put the traditional control charts in trouble. The mixed EWMA-CUSUM (MEC) control chart and the ARMA control chart are effective tools to monitor the mean of autocorrelated processes. This paper proposes an integrated model subject to some constraints for determining the decision variables of triple concepts in the presence of autocorrelated data. Three types of autocorrelated processes are investigated to study their effects on the results. Moreover, the results of the MEC and ARMA charts are compared. Due to the complexity of the model, a particle swarm optimization (PSO) algorithm is applied to select optimal decision variables. An industrial example and extensive comparisons are provided

---

Productions of the industries around the world depend on using equipment and machines. Therefore, it is vital to support the supply of equipment and spare parts for maintenance operations, especially in strategic industries that separate optimization of inventory management, supplier selection, network design, and planning decisions may lead to sub-optimal solutions. The integration of forward and reverse spare part logistics network can help optimize total costs. In this paper, a  mathematical model is presented for designing and planning an integrated forward-reverse repairable spare parts supply chain to make optimal decisions. The model considers the uncertainty in demand during the lead-time and the optimal assignment of repairable equipment to inspection, disassembly, and repair centers. A METRIC (Multi-Echelon Technique for recoverable Item Control) model is integrated into the forward-reverse supply chain to handle inventory management. A case study of National Iranian Oil Company (NIOC) is presented to validate the model. The non-linear constraints are linearized by using a linearization technique; then the model is solved by an iterative procedure in GAMS. A prominent outcome of the analyses shows that the same policies for repair and purchase of all the equipment and spare parts do not result in optimal solutions. Also, considering supply, repair, and inventory management decisions of spare parts simultaneously helps decision-makers enhance the supply chain's performance by applying a well-balanced repairing and purchasing policy.

---

The role of sustainability dimensions in the value creation process has received much attention. Adopting a proper set of key performance indicators sustainability leads to accurate calculation of chain value. This paper focuses on the dimensions of in the biofuel supply chain and seeks to evaluate the value in the chain. First, the importance of biofuels and its various types are discussed. Then, a new model is presented by designing the proposed energy chain and considering its sustainability dimensions and indicators in uncertain environment. Rough set theory is one of the best mathematical tools for dealing with uncertainty. The proposed biofuel energy supply chain is modeled to obtain the total value of the system considering sustainability indicators and layers of the supply chain. A multi-objective rough mathematical formulation is presented and solved. Best-worst method was integrated to determine the significance score of sustainability indicators. Finally, the model of the rough linear mathematical program is solved with optimization tools and the sustainable value of the chain is obtained.

---

This study seeks to introduce the influential factors in controlling and dealing with uncertainty in intermittent demand. Hybrid forecasting and Grey Theory, due to their potential in facing complex nature, insufficient data, have been used simultaneously. Different modeling, unbiased weighting results have been used in estimating the safety stock(SS) by both theoretical and experimental methods. In other words, this work deals with the less studied feature of various modeling errors and their effect on SS determination and recommends its use to address the uncertainty of intermittent demand as a criterion for introducing a superior model in the field of inventory.

---

Drawing lessons from the Covid-19 pandemic according to literature, this contribution aims to show that greening the United Nations System with stronger environmental considerations, can help to shift the global economy from fossil energy to renewable energy with public-health resilient systems. This contribution starts with highlighting the fact that past economic crises and the implementation of the Sustainable Development Global Agenda have not been able to generate strong institutional arrangements for sustainable development including climate resilience building and public health resilient systems. This allows us to apprehend the possibility that the Covid-19 pandemic crisis may face the same incapacity. In response to these statements, this contribution shares the opinion that institutional reforms within the United Nations System may lead to perennial normative provisions and institutional arrangements able to make sustainable development happen with resilient public-health systems. This note highlights the fall of GHZ emissions during the Covid-19 pandemic. It shows, however, based on the history of the past crisis, that the huge investment being mobilized to recover from the pandemic can quickly absorb GHZ emissions fall. The way out suggested is that both the Global Economy and the Global Public Health agendas can be revisited to be strengthened by stronger environmental considerations. One of our findings is that multilateralism can adopt suitable institutional arrangements in Global Environmental Governance throughout the current global agenda on International Environmental Governance Reform within the United Nations System.

---

The health insurance system can play an effective role to control health expenditures. The purpose of this study is to provide a model for estimating the physician visit tariffs. To achieve this goal, a hybrid model was used. fuzzy logic is the most appropriate tool for controlling systems and deriving rules for the relationship between inputs and outputs. So, the output of the data mining techniques enter the fuzzy logic as an input variable. The data were collected from the Health Insurance Organization of Iran in two sections including the physicians' costs and physicians' deductions. Owing to the techniques used in this model, NN had the least error, as compared to other data mining techniques (0.0034 and 0.0013, respectively). After defining the variables, membership functions and fuzzy logic rules, the accuracy of the whole control model was confirmed by random data. This research has dealt with the domains of health insurance , their connections and defining effective variables better and more extensively than the other studies in the field.

---

Nowadays, supply chain management (SCM) is an interesting problem that has attracted the attention of many researchers. Transportation network design is one of the most important fields of SCM. In this paper, a logistics network design is considered to optimize the total cost and increase the network stability and resiliency. First, a mixed integer nonlinear programming model (MINLP) is formulated to minimize the transportation time and transportation cost of products. The proposed model consists of two main stages.
One is a normal stage that minimizes the transportation and holding costs, all manufacturers are also assumed to be healthy and in service. In this stage, the quantity of customer demand met by each manufacturer is eventually determined.
The second is the resilience stage. A method is presented by creating an information network in this supply chain for achieving the resilient and sustainable production and distribution chain that, if some manufacturers break down or stop production, Using the Restarting and load sharing scenarios in the reactive approach to increase resilience with accepting the costs associated with it in the supply network and return to the original state in the shortest possible time, the consequences of accidental failure and shutdown of production units are managed.
Two capacities are also provided for each manufacturer

• Normal capacity to meet the producer's own demand
• Load sharing capacity, Determine the empty capacity and increase the capacity of alternative units to meet the out-of-service units demand

In order to solve the model, we used GAMS & Matlab software to find the optimal solutions. A hybrid priority-based Non-dominated Sorting Genetic Algorithms (NSGA-II) and Sub-population Genetic Algorithm (SPGA- II) is provided in two phases to find the optimal solutions. The solutions are represented with a priority matrix and an Allocated vector. To compare the efficiency of two algorithms several criteria are used such as NPS, CS and HV. Several Sample problems are generated and solved that show the Sub-population Genetic Algorithm (SPGA- II) can find good solutions in a reasonable time limit.