International Journal of Industrial Engineering & Production Research

---

---

Local bus network is the most popular transit mode and the only available transit mode in the majority of cities of the world. Increasing the utility of this mode which increases its share from urban trips is an important goal for city planners. Timetable setting as the second component of bus network design problem (network route design timetable setting vehicle assignment crew assignment) have a great impact on total travel time of transit passengers. The total travel time would effect on transit utility and transit share of urban trips. One of the most important issues in timetable setting is the temporal coverage of service during the day. The coverage of demand is an objective for setting timetables which has not been well studied in the literature. In this paper a model is developed in order to maximize the temporal coverage of bus network. The model considers demand variation during the day as well as the stochastic nature of demand. A distribution function is used instead of a deterministic value for demand. The model is then implemented to an imaginary case.

---

Evaluative and comparative analysis among educational projects remains an issue for administration, program directors, instructors, and educational institutes. This study reports a fuzzy complexity model for educational projects, which has two primary aspects (technical aspects and transparency aspects). These aspects may not be measured precisely due to uncertain situations. Therefore, a fuzzy graph-based model to measure the relative complexity of educational projects is presented that uses an aggregation operator to resolve conflict among experts with respect to a complexity relation. The model maps the fuzzy graph into a scaled Cartesian diagram that depicts the relative degree of complexity among projects. An illustrative example for several educational projects is demonstrated to present the application of the model.

---

Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumers' demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.

---

The ever severe dynamic competitive environment has led to increasing complexity of strategic decision making in giant organizations. Strategy formulation is one of basic processes in achieving long range goals. Since, in ordinary methods considering all factors and their significance in accomplishing individual goals are almost impossible. Here, a new approach based on clustering method is proposed to assist the decision makers in formulating strategies. Having extracted the internal and external factors, after setting long range goals, the factor-goal matrices are generated according to the impact rate of factors on goals. According to created matrices, clusters including goals and factors are formed. By considering individual clusters the strategies are proposed according to the current state of clusters for the organization. By applying this new method the opportunity of considering the impact of all factors and its interactions on goals are not lost. Strategy-factor and strategy-goal matrices are utilized to validate the proposed method. To show the appropriateness and practicality of our approach, particularly in an environment with a large number of interacting goals and factors, we have implemented the approach in Mahmodabad Training Center (MTC) in Iran. The resulting goal-factor, current and dated states of clusters, also, strategy-goal and strategy-factor matrices for model validation and route branch indices for finding out how the organization achieved each goal are reported.

---

The existing works considering the flow-based discount factor in the hub and spoke problems, assume that increasing the amount of flow passing through each edge of network continuously decreases the unit flow transportation cost. Although a higher volume of flow allows for using wider links and consequently cheaper transportation, but the unit of flow enjoys more discounts, quite like replacing the current link by a cheaper link type (i.e., increasing the volume of flow without changing the link type would not affects the unit flow transportation cost). Here, we take a new approach, introducing multi-level capacities to design hub and spoke networks, while alternative links with known capacities, installation costs and discount factors are available to be installed on each network edge. The flow transportation cost and link installation cost are calculated according to the type of links installed on the network edges thus, not only the correct optimum hub location and spoke allocation is determined, but also the appropriate link type to be installed on the network edges are specified. The capacitated multiple allocation p-hub median problem (CMApHMP) using the multi-level capacity approach is then formulated as a mixed-integer linear program (MILP). We also present a new MILP for the hub location problem using a similar approach in order to restrict the amount of flow transmitting through the hubs. Defining diseconomies of scale for each hub type, the model is to present congestion at the hubs and balance the transmitting flow between the hubs. Two new formulations are presented for both the p-hub median and the hub location problems which requiring a flow between two non-hub nodes to be transferred directly, when a direct link between the nodes is available. These models are useful for the general cost structure where the costs are not required to satisfy the triangular inequality. Direct links between non-hub nodes are allowed in all the proposed formulations.

---

Identification of a real time of a change in a process, when an out-of-control signal is present is significant. This may reduce costs of defective products as well as the time of exploring and fixing the cause of defects. Another popular topic in the Statistical Process Control (SPC) is profile monitoring, where knowing the distribution of one or more quality characteristics may not be appropriate for discussing the quality of processes or products. One, rather, uses a relationship between a response variable and one or more explanatory variable for this purpose. In this paper, the concept of Maximum Likelihood Estimator (MLE) applied to estimate of the change point in binary profiles, when the type of change is drift. Simulation studies are provided to evaluate the effectiveness of the change point estimator.

---

The main goal in this paper is to propose an optimization model for determining the structure of a series-parallel system. Regarding the previous studies in series-parallel systems, the main contribution of this study is to expand the redundancy allocation parallel to systems that have repairable components. The considered optimization model has two objectives: maximizing the system mean time to first failure and minimizing the total cost of the system. The main constraints of the model are: maximum number of the components in the system, maximum and minimum number of components in each subsystem and total weight of the system. After establishing the optimization model, a multi objective approach of Imperialist Competitive Algorithm is proposed to solve the model.

---

Having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. In this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors of the supply chain. At the first step, indicators were determined and explained by explanatory Factor Analysis. Then, Network Data Envelopment Analysis (NDEA) model was used. This paper is the result of research related to supply chain of pharmaceutical companies in Tehran Stock Exchange and 115 experts and senior executives have been questioned as sample. The results showed that responsiveness latent variable had the highest correlation with supply chain performance and collaborative, financial and intellectual capital (knowledge base) latent variables were respectively after that. Four of the twenty eight supply chains which were studied obtained 1 as the highest performance rate and the lowest observed performance was 0.43.

---

In this paper, a new approach based on game theory has been proposed to multi responses problem optimization. Game theory is a useful tool for decision making in the conflict of interests between intelligent players in order to select the best joint strategy for them through selecting the best joint desirability. Present research uses the game theory approach via definition of each response as each player and factors as strategies of each player. This approach cans determine the best predictor factor sets in order to obtain the best joint desirability of responses. For this aim, the signal to noise ratio(SN) index for each response have been calculated with considering the joint values of strategies then obtained SN ratios for each strategy is modeled in the game theory table. Finally, using Nash Equilibrium method, the best strategy which is the best values of predictor factors is determined. A real case and a numerical example are given to show the efficiency of the proposed method. In addition, the performance of the proposed method is compared with the VIKOR method.

---

Abstract One of the basic assumptions in hub covering problems is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. Practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. Change in problem parameters during the planning horizon is one of the key factors causing the results of theoretical models to be impractical in real world situations. To dissolve this problem in this paper a mathematical model for dynamic single allocation hub covering problem is proposed in which the covering radius of hub nodes is one of the decision variables. Also Due to NP-Hardness of the problem and huge computational time required to solve the problem optimally an effective genetic algorithm with dynamic operators is proposed afterwards. Computational results show the satisfying performance of the proposed genetic algorithm in achieving satisfactory results in a reasonable time. Keywords: hub location problem, dynamic hub covering problem, flexible covering radius, dynamic genetic algorithm.

---

This paper addresses a reliable facility location problem with considering facility capacity constraints. In reliable facility location problem some facilities may become unavailable from time to time. If a facility fails, its clients should refer to other facilities by paying the cost of retransfer to these facilities. Hence, the fail of facilities leads to disruptions in facility location decisions and this problem is an attempt to reducing the impact of these disruptions. In order to formulate the problem, a new mixed-integer nonlinear programming (MINLP) model with the objective of minimizing total investment and operational costs is presented. Due to complexity of MINLP model, two different heuristic procedures based on mathematical model are developed. Finally, the performance of the proposed heuristic methods is evaluated through executive numerical example. The numerical results show that the proposed heuristic methods are efficient and provide suitable solutions.

---

The concept of "complexity" is familiar to most of project's managers, but it is not comprehended in the same way. although the complexity highlights negative points, but it may bring positive advantages which support the project. Researches conducted on this field show that the understanding of "complexity" between the researchers is different and it is mainly depends on their points of view. In fact, many identified aspects of the complexity in the literature are related to the aims of the research. In this paper, an attempt was made to describe the positive / negative features of the complexity of project using three approaches research literature (manufacturing and project complexity), interviews (deep interview with 20 experts) and questionnaire. The research was conducted on the Complex product and system (CoPS) projects. in addition, WH question technique was used. In conclusion, a 5p model (Purpose, Product, Process, People, Peripheral) has been introduced as the outcome of the study.

---

Scheduling has become an attractive area for artificial intelligence researchers. On other hand, in today's real-world manufacturing systems, the importance of an efficient maintenance schedule program cannot be ignored because it plays an important role in the success of manufacturing facilities. A maintenance program may be considered as the heath care of manufacturing machines and equipments. It is required to effectively reduce wastes and have an efficient, continuous manufacturing operation. The cost of preventive maintenance is very small when it is compared to the cost of a major breakdown. However, most of manufacturers suffer from lack of a total maintenance plan for their crucial manufacturing systems. Hence, in this paper, we study a maintenance operations planning optimization on a realistic variant of parallel batch machines manufacturing system which considers non-identical parallel processing machines with non-identical job sizes and fixed/flexible maintenance operations. To reach an appropriate maintenance schedule, we propose solution frameworks based on an Artificial Immune Algorithm (AIA), as an intelligent decision making technique. We then introduce a new method to calculate the affinity value by using an adjustment rate. Finally, the performance of proposed methods are investigated. Computational experiments, for a wide range of test problems, are carried out in order to evaluate the performance of methods.

---

In the recent decade, special attention is paid to reverse logistic due to economic benefits of recovery and recycling of used products as well as environmental legislation and social concerns. On the other hand، many researches claim that separately and sequential planning of forward and reverse logistic causes sub-optimality. Effective transport activities are also one of the most important components of a logistic system and it needs an accurate planning. In this study, a mixed integer linear programming model is proposed for integrated forward / reverse supply chain as well as vehicles routing. Logistic network which is used in this paper is a multi-echelon integrated forward /reverse logistic network which is comprised capacitated facility, common facilities of production/recovery and distribution/collection, disposal facilities and customers. The proposed model is multi-period and multi-product with the ability to consider several facilities in each level. Various types of vehicle routing models are also included such as multi-period routing, multi-depot, multi-products, routing with simultaneous delivery and pick-up, flexible depot assignment and split delivery. The model results present the product flow between the various facilities in forward and reverse direction throughout the planning horizon with the objective minimization of total cost. Numerical example for solving the model using GAMS shows that the proposed model could reach the optimal solution in reasonable time for small and medium real world’s problems.  

---

In this paper, we propose a vibration damping optimization algorithm to solve a fuzzy mathematical model for the single-item capacitated lot-sizing problem. At first, a fuzzy mathematical model for the single-item capacitated lot-sizing problem is presented. The possibility approach is chosen to convert the fuzzy mathematical model to crisp mathematical model. The obtained crisp model is in the form of mixed integer linear programming (MILP) which can be solved by existing solver in crisp environment to find optimal solution. Due to the complexity and NP-hardness of the problem, a vibration damping optimization (VDO) is used to solve the model for large-scale problems.  To verify the performance of the proposed algorithm, we computationally compared the results obtained by the VDO algorithm with the results of the branch-and-bound method and two other well-known meta-heuristic algorithms namely simulated annealing (SA) and genetic algorithm (GA). Additionally, Taguchi method is used to calibrate the parameters of the meta-heuristic algorithms. Computational results on a set of randomly generated instances show that the VDO algorithm compared with the other algorithms can obtain appropriate solutions.

---

Recently, sustainable supply chain management (SSCM) has become one of the important subjects in the industry and academia. Supplier selection, as a strategic decision, plays a significant role in SSCM. Researchers use different multi-criteria decision making (MCDM) methods to evaluate and select sustainable suppliers. In the previous studies, evaluation is solely based on the desirable features of suppliers and their risks are neglected. Therefore, current research uses failure mode and effects analysis (FMEA) as a risk analysis technique to consider supplier's risk in combination with the MCDM method. Practically, this study operated in two main stages. In the first stage, the score of the suppliers obtains by integration Fuzzy MOORA and FMEA. In the second stage, the output of the previous stage used as input parameters in developed mix-integer linear programming to select suppliers and order optimum quantity. Finally, to demonstrate the effectiveness of the proposed approach, a case study in a chemical industry and sensitivity analysis is presented.  

---

Today, many companies after achieving improvements in manufacturing operations are focused on the improvement of distribution systems and have long been a strong tendency to optimize the distribution network in order to reduce logistics costs that the debate has become challenging. Improve the flow of materials, an activity considered essential to increase customer satisfaction. In this study, we benefit cross docking method for effective control of cargo flow to reduce inventory and improve customer satisfaction. Also every supply chain is faced with risks that threaten its ability to work effectively. Many of these risks are not in control but can cause great disruption and costs for the supply chain process. In this study we are looking for a model to collect and deliver the demands for the limited capacity vehicle in terms of disruption risk finally presented a compromised planning process. In fact, we propose a framework which can consider all the problems on the crisis situation for decision-making in these conditions, by preparing a mathematical model and software gams for the following situation in a case study. In the first step, the results presented in mode of a two-level planning then the problem expressed in form of a multi-objective optimization model and the results was explained.

---

Considering the high costs of the implementation and maintenance of gas distribution networks in urban areas, optimal design of such networks is vital. Today, urban gas networks are implemented within a tree structure. These networks receive gas from City Gate Stations (CGS) and deliver it to the consumers. This study presents a comprehensive model based on Mixed Integer Nonlinear Programming (MINLP) for the design of urban gas networks taking into account topological limitations, gas pressure and velocity limitations and environmental limitations. An Ant Colony Optimization (ACO) algorithm is presented for solving the problem and the results obtained by an implementation of ACO algorithm are compared with the ones obtained through an iterative method to demonstrate the efficiency of ACO algorithm. A case study of a real situation (gas distribution in Kelardasht, Iran) affirms the efficacy of the proposed approach.
 

---

Nowadays, several methods in production management mainly focus on the different partners of supply chain management. In real world, the capacity of planes is limited. In addition, the recent decade has seen the rapid development of controlling the uncertainty in the production scheduling configurations along with proposing novel solution approaches. This paper proposes a new mathematical model via strong recent meta-heuristics planning. This study firstly develops and coordinates the integrated air transportation and production scheduling problem with time windows and due date time in Fuzzy environment to minimize the total cost. Since the problem is NP-hard, we use four meta-heuristics along with some new procedures and operators to solve the problem. The algorithms are divided into two groups: traditional and recent ones. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as traditional algorithms, also Keshtel Algorithm (KA) and Virus Colony Search (VCS) as the recent ones are utilized in this study. In addition, by using Taguchi experimental design, the algorithm parameters are tuned. Besides, to study the behavior of the algorithms, different problem sizes are generated and the results are compared and discussed.