ORIGINAL_ARTICLE An Empirical Investigation of the Universal Effectiveness of Quality Management Practices: A Structural Equation Modeling Approach Institutional theory argues that the isomorphic nature of quality management (QM) practices leads to similar QM implementation and performance among QM-embedded firms. However, contingency theory questions such 'universal effectiveness of QM practices'. Considering these conflicting arguments, this study tests samples from the U.S. and China to examine whether the 'universal effectiveness of QM practices’ across national boundaries actually exists. First, the confirmatory factor analysis was performed to examine the validity of the survey instruments developed in this study. Then, the hypotheses were tested using the structural equation modeling (SEM) analysis. The SEM test results indicated that the positive effect of behavioral QM on firm performance was more significant in the U.S. sample than in the China sample. The test results also presented that the relative effect of behavioral QM versus technical QM on firm performance was noticeably different in service firms, according to national economic maturity. The study’s findings demonstrated that a firm's contingency factors, such as national economic maturity and industry type, could result in the heterogeneous implementation of the firm’s TQM program; consequently, the findings weakened the 'universal effectiveness of QM practices'. http://www.ijsom.com/article_2668_7577aa9c44074a5d94bda84985d1d828.pdf 2016-05-01 1102 1111 10.22034/2016.1.01 Quality management Contingency theory Survey research Factor analysis Structural equation modeling Young Sik Cho young_sik.cho@jsums.edu 1 College of Business, Jackson State University, Mississippi, USA LEAD_AUTHOR Ramin Maysami ramin.c.maysami@jsums.edu 2 College of Business, Jackson State University, Mississippi, USA AUTHOR Joo Jung joo.jung@utrgv.edu 3 College of Business and Entrepreneurship, The University of Texas, USA AUTHOR C. Christopher Lee christopher.lee@ccsu.edu 4 School of Business, Central Connecticut State University, USA AUTHOR Akgün, A. E., Ince, H., Imamoglu, S. 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ORIGINAL_ARTICLE An Integrated Enterprise Resources Planning (ERP) Framework forFlexible Manufacturing SystemsUsing Business Intelligence (BI)Tools Nowadays Business intelligence (BI) tools provide optimal decision making, analyzing, controlling and monitoring of operations in enterprise systems like enterprise resource planning (ERP) and mainly refer to strong decision making methods used in online analytical processing, reporting and data analysis, such as improve internal processes, analysis of resources, information needs analysis, reduce costs and increase revenue. The main purpose of paper is creating a unified framework for the application of BI in ERP systems which results of value-added inflexible manufacturing systems (FMS). In this paper, business process system and interaction between technology and environment byapplying BI in ERPsystems of companies that use flexible manufacturing systems have been presented. This paper is a comprehensive review of recent literature that examined the effects of BI systems on the fourlevels of Tenhialaet al.' Model (2015).This model based on cross-sectional data from 151 manufacturing plants proved that ERP is essential for the FMS. According to results of this paper, the answer to this question is important “How can we use the potential data, and intelligence of BI in ERP systems for the effective flexible manufacturing systems?” This study has four hypotheses to answer this question and based on results, all four hypotheses were confirmed. Finally, a model has been developed to determine the relationship between BI (as enabler of ERP) and FMS. http://www.ijsom.com/article_2659_8f8e8dc8feb2f2bd82a328728645e2a4.pdf 2016-05-01 1112 1125 10.22034/2016.1.02 Business Intelligence (BI) Enterprise Resource Planning flexible manufacturing systems (FMS) Smart Management Decision Support Systems Mehrdad Nouri Koupaei mhrdd_nouri@yahoo.com 1 Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran AUTHOR Mohammad Mohammadi mohammad_9091@yahoo.com 2 Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran LEAD_AUTHOR Bahman Naderi bahman_naderi62@yahoo.com 3 Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran AUTHOR Azma. F. and Mostafapour. M. A., (2012). Business intelligence as a key strategy for development organizations. Procedia Technology, Vol. 1, pp. 102-106. 1 Cheng. H., Lu. Y. C., and Sheu. C., (2009). An ontology-based business intelligence application in a financial knowledge management system, Expert Systems with Applications, Vol. 36(2), pp. 3614-3622. 2 Cochran. W. G., (1977). Sampling techniques (3rd ed.), New York: John Wiley & Sons. 3 Collins. R.S., Schmenner. R., (1993). Achieving rigid flexibility: Factory focus for the 1990s, European Management Journal, Vol. 11 (4), pp. 443-447. 4 Elbashir. M. Z., Collier. P. A. and Davern. M. J., (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, Vol. 9(3), pp. 135-153. 5 Ghazanfari. M., Jafari. M. and Rouhani. S., (2011). A tool to evaluate the business intelligence of enterprise systems, Scientia Iranica, Vol. 18 (6), pp. 1579–1590. 6 Goodale. J.C., Kuratko. D.F., Hornsby. J.S. and Covin. J.G., (2011). Operations management and corporate entrepreneurship: The moderating effect of operations control on the antecedents of corporate entrepreneurial activity in relation to innovation performance, Journal of Operations Management, Vol. 29 (1-2), pp. 116-127. 7 Gosling. J., Purvis. L., Naim. M. M., (2010). Supply chain flexibility as a determinant of supplier selection, International Journal of Production Economics, Vol. 128 (1), pp. 11–21. 8 Huang. X., Kristal. M. M., Schroeder. R. G., (2010). The impact of organizational structure on mass customization capability: A contingency view, Production and Operations Management, Vol. 19 (5), pp. 515-530. 9 Jacobs. M., (2008). Product Complexity: Theoretical Relationships to Demand and Supply Chain Costs, Publisher: ProQuest LLC. 10 Jiang. P., Zhang. C., Leng. J. and Zhang. J., (2015). Implementing a WebAPP-based Software Framework for Manufacturing Execution Systems, IFAC-PapersOnLine, Vol. 48 (3), pp. 388–393. 11 Jiang. 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ORIGINAL_ARTICLE Smart City Reference Model: Interconnectivity for On-Demand User to Service Authentication The Internet of Things and Services (IoTS) has encouraged the development of service provisioning systems in respect to Smart City topics. Most of them are operated as heterogeneous systems which limits end customers’ access and contradicts with IoTS principles. In this paper, we discuss and develop a reference model of an interconnected service marketplace ecosystem. The prototypical implementation incorporates findings from an empirical study and lessons learned from research projects. The elaborated ecosystem enables service request roaming between different parties across system boundaries. The paper presents a feasible centralized architecture, introduces involved parties and parts of a developed message protocol. Why a contracting mechanism is indispensable for request roaming is also outlined. The model’s feasibility is demonstrated by means of a current electric mobility use case: providing access to foreign charging infrastructure without multiple registrations. This work contributes to simplify the data exchange between service platforms to improve Smart City solutions and to support travelers with intelligent mobility applications. http://www.ijsom.com/article_2667_df336e72104d76528eade4a68ad1b21b.pdf 2016-05-01 1126 1142 10.22034/2016.1.03 Smart City Interconnected Services Connected Mobility Internet of Things and Services Fragmented Service Solutions Michael Strasser michael.strasser@bosch-si.com 1 Bosch Software Innovations, Technical University, Berlin, Germany LEAD_AUTHOR Sahin Albayrak sahin.albayrak@dai-labor.de 2 Distributed Artificial Intelligence Laboratory, Technical University Berlin, Berlin, Germany AUTHOR ALL, T. (2013). Collaborative Open Market to Place Objects at your Service. compose-project.eu. 1 Balakrishna, C. (2012). Enabling technologies for smart city services and applications. In Proceedings of the 6th International Conference on Next Generation Mobile Applications, Services, and Technologies, NGMAST, pp. 223–227. doi:10.1109/NGMAST.2012.51 2 Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J., Mellouli, S., Nahon, K., … Scholl, H. (2012). Understanding Smart Cities: An Integrative Framework Hafedh. In 45th Hawaii International Conference on System Science (HICSS), pp. 2289–2297. 3 Christ, P., Hahn, C., Henze, S., Hesse, T., Kaul, R., Kazubski, S.,Weiner, N. (2015). Good E-Roaming Practice. Begleit- und Wirkungsforschung Schaufenster Elektromobilität (BuW). 4 Dirks, S., & Keeling, M. (2009). A vision of smarter cities: How cities can lead the way into a prosperous and sustainable future. IBM Institute for Business Value. June, 1–6. 5 Fricke, V., Dannhauer, A., Schilling, R., Stiffel, D. T., Reschauer, D. N., Gereke, T., … Coppola, V. (2012). 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ORIGINAL_ARTICLE Robust Optimization Approach for Design for a Dynamic Cell Formation Considering Labor Utilization: Bi-objective Mathematical Model In this paper, robust optimization of a bi-objective mathematical model in a dynamic cell formation problem considering labor utilization with uncertain data is carried out. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. In this research, cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer programming (MIP) model is developed to formulate the related robust dynamic cell formation problem. Then the problem is transformed into a bi-objective linear one. The first objective function seeks to minimize relevant costs of the problem including machine procurement and relocation costs, machine variable cost, inter-cell movement and intra-cell movement costs, overtime cost and labor shifting cost between cells, machine maintenance cost, inventory, holding part cost. The second objective function seeks to minimize total man-hour deviations between cells or indeed labor utilization of the modeled. http://www.ijsom.com/article_2660_f316d813d31f75fe2b48091e8841e4a6.pdf 2016-05-01 1143 1167 10.22034/2016.1.04 Dynamic Cellular Manufacturing Robust optimization man-hour deviations bi-objective mathematical model Hiwa Farughi h.farugh@uok.ac.ir 1 Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran LEAD_AUTHOR Sobhan Mostafayi s.mostafayi@eng.uok.ac.ir 2 Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran AUTHOR Aalaei, Amin, and Hamid Davoudpour. 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ORIGINAL_ARTICLE Inventory Model for Non – Instantaneous Deteriorating Items, Stock Dependent Demand, Partial Backlogging, and Inflation over a Finite Time Horizon In the present study, the Economic Order Quantity (EOQ) model of two-warehouse deals with non-instantaneous deteriorating items, the demand rate considered as stock dependent and model affected by inflation under the pattern of time value of money over a finite planning horizon. Shortages are allowed and partially backordered depending on the waiting time for the next replenishment. The main objective of this work is to minimize the total inventory cost and finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented. http://www.ijsom.com/article_2666_3f09fbf2e0e14cd3bdb99a9d5c52966a.pdf 2016-05-01 1168 1191 10.22034/2016.1.05 Two-warehouse Partial backlogging Stock-dependent demand Inflation Deterioration Shortages Neeraj Kumar nkneerajkapil@gmail.com 1 SRM University, Delhi - NCR, Sonepat, Haryana, India LEAD_AUTHOR Sanjey Kumar sanjey_singh@rediffmail.com 2 SRM University, Delhi - NCR, Sonepat, Haryana, India AUTHOR Buzacott, JA. , (1975). Economic order quantities with inflation. Operations Research Quarterly, Vol. 26(3), pp. 553–558.  1 Chang, CT., Teng, JT., & Goyal, SK., (2010). Optimal replenishment policies for non-instantaneous deteriorating items with stock-dependent demand. International Journal of Production Economics, Vol. 123(1), pp. 62–68. 2 Cheng, M., Zhang, B., & Wang, G., (2011). Optimal policy for deteriorating items with trapezoidal type demand and partial backlogging. Applied Mathematical Modelling, 35(7), 3552–3560. Chung, K.J., (1996). Optimal ordering time interval taking account of time value. Production Planning and Control, Vol. 7(3), pp. 264–267. 3 Chung, K.J., (2009). A complete proof on the solution procedure for non-instantaneous deteriorating items with permissible delay in payment. Computers & Industrial Engineering, Vol. 56(1), pp. 267–273. 4 Data, T.K., Pal, A.K., (1991). Effects of inflation and time value of money on an inventory model with linear time dependent demand rate and shortages. European Journal of Operational Research, Vol. 52(3), pp. 326–333. 5 Deb, M., Chaudhuri, K.S., (1986). An EOQ model for items with finite rate of production and variable rate of deterioration. Opsearch, Vol. 23(1), pp. 175-181. 6 Dye, C.Y., (2013). The effect of preservation technology investment on a non-instantaneous deteriorating inventory model. Omega, Vol. 41(5), pp. 872–880. 7 Dye, C.Y., Ouyang, L.Y., & Hsieh, T.P., (2007). Deterministic inventory model for deteriorating items with capacity constraint and time-proportional backlogging rate. European Journal of Operational research, Vol. 178(3), pp. 789-807. 8 Geetha, K.V., Uthayakumar, R., (2009). Economic design of an inventory policy for non-instantaneous deteriorating items under permissible delay in payments. Journal of Computational and Applied Mathematics, Vol. 233(10), pp. 2492-2505. 9 Ghare, P.M., Schrader, G.H., (1963). A model for exponentially decaying inventory system. International Journal of Production Research, Vol. 21, pp. 449-460. 10 Goyal, S.K., Giri, B.C., (2001). Recent trends in modeling of deteriorating inventory. European Journal of Operational Research, Vol. 134(1), pp. 1-16. 11 Guchhaita, P., Maiti , M. K., & Maiti, M., (2013). Two storage inventory model of a deteriorating item with variable demand under partial credit period. Applied Soft Computing, Vol. 13(1), pp. 428–448. 12 Guria, A., Das, B., Mondal, S., & Maiti, M., (2013). Inventory policy for an item with inflation induced purchasing price, selling price and demand with immediate part payment. Applied Mathematical Modelling, Vol. 37(1), pp. 240–257. 13 Hartley R.V. (1976). Operations Research—A Managerial Emphasis. Good Year Publishing Company, California, pp. 315-317. 14 Hou KL, Lin LC (2006) An EOQ model for deteriorating items with price- and stock-dependent selling rates under inflation and time value of money. International Journal of Systems Science, Vol. 37, pp. 1131-1139. 15 Hsieh TP, Dye CY, Ouyang LY (2008) determining optimal lot size for a two-warehouse system with deterioration and shortages using net present value. European Journal of Operational Research, Vol. 191, pp. 182–192. 16 Kumar N, Singh S R, Kumari R (2008) a Two-Warehouse inventory model without shortage for exponential demand rate and an optimum release rule. Ultra Scientist of Physical Sciences, Vol. 20, pp. 395-402. 17 Kumar N and Kumar S (2016) Effect of learning and salvage worth on an inventory model for deteriorating items with inventory-dependent demand rate and partial backlogging with capability constraints. Uncertain Supply Chain Management, Vol. 4, pp. 123-136. 18 Kumar N, Singh S R, Kumari R (2011) a deterministic Two-warehouse Inventory Model for Deteriorating Items with Sock-dependent Demand and Shortages under the Conditions of Permissible Delay. International Journal of Mathematical Modeling and Numerical Optimizations, Vol. 11, pp. 357-375. 19 Kumar N, Singh S R, Kumari R (2013) Learning effect on an inventory model with two-level storage and partial backlogging under inflation. International Journal of Services and Operations Management, Vol. 16, pp. 105–122. 20 Kumar N, Singh S R, Kumari R (2014) Effect of Salvage Value on a Two-Warehouse Inventory Model for Deteriorating Items with Stock-Dependent Demand Rate and Partial Backlogging .International Journal of Operational Research, Vol. 19, pp. 479–496. 21 Lee C, Ma C (2000) optimal inventory policy for deteriorating items with two-warehouse and timedependent demands. Production Planning and Control, Vol. 11, pp. 689–696. 22 Liao J (2008) An EOQ model with non-instantaneous receipt and exponential deteriorating item under two-level trade credit. International Journal of Production Economics, Vol. 113, pp. 852–861 23 Maihami R, Abadi INK (2012a) Joint control of inventory and its pricing for non-instantaneously deteriorating items under permissible delay in payments and partial backlogging. Mathematical and Computer Modelling, Vol. 55, pp. 1722–1733. 24 Maihami R, Kamalabadi IN (2012b) Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand. International. Journal of Production Economics, Vol. 136, pp. 116–122. 25 Min J, Zhou YW (2009) a perishable inventory model under stock-dependent selling rate and shortage dependent partial backlogging with capacity constraint. International Journal of Systems Science, Vol. 40, pp. 33-44. 26 Misra RB (1979) A note on optical inventory management under inflation. Naval Research Logistics Quarterly, Vol.  26, pp. 161–165. 27 Ouyang LY, Wu KS, Yang CT (2006) A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers & Industrial Engineering, Vol. 51, pp. 637–651. 28 Pakkala, T.P.M., Achary, K.K., (1992). A deterministic inventory model for deteriorating items with two warehouses and finite replenishment rate. European Journal of Operational Research, Vol. 57, pp. 71-76. 29 Philip GC (1974) A generalized EOQ model for items with weibull distribution. AIIE Transactions, Vol. 6, pp.159-162. 30 Ray J, Chaudhuri KS (1997) An EOQ model with stock-dependent demand, shortage, inflation and time discounting. International Journal of Production Economics, Vol. 53, pp. 171-180. 31 Roy MD, Sana SS, and Chaudhuri KS (2011) An economic order quantity model of imperfect quality items with partial backlogging. International Journal of Systems Science, Vol. 42, pp. 1409-1419. 32 Sarkar B, Sarkar S (2013) An improved inventory model with partial backlogging, time varying deterioration and stock-dependent demand. Economic Modelling, Vol. 30, pp. 924–932. 33 Sarkar T, Ghosh SK, Chaudhuri KS (2012) An optimal inventory replenishment policy for a deteriorating item with time-quadratic demand and time-dependent partial backlogging with shortages in all cycles. Applied Mathematics and Computation, Vol. 218, pp. 9147–9155. 34 Sarker BR, Pan H (1994) Effects of inflation and time value of money on order quantity and allowable shortage. International Journal of Production Economics, Vol. 34, pp. 65–72. 35 Sarma KVS (1983) A deterministic inventory model with two levels of storage and an optimum release rule. Opsearch 20:175-180. Sarma KVS, Sastry MP (1988) Optimum inventory for systems with two levels of storage. Industrial Engineering Journal, Vol. 8, pp. 12-19. 36 Sett BK, Sarkar B, Goswami A (2012) A two-warehouse inventory model with increasing demand and time varying deterioration. 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ORIGINAL_ARTICLE The Inventory System Management under Uncertain Conditions and Time Value of Money This study develops a inventory model to determine ordering policy for deteriorating items with shortages under markovian inflationary conditions. Markov processes include process whose future behavior cannot be accurately predicted from its past behavior (except the current or present behavior) and which involves random chance or probability. Behavior of business or economy, flow of traffic, progress of an epidemic, all are examples of Markov processes. Since the far previous inflation rate don’t have a great impact on the current inflation rate, so, It is logical to consider changes of the inflation rate as a markov process. In addition, It is assumed that the cost of the items changes as a Continuous – Time - Markov Process too. The inventory model is described by differential equations over the time horizon along with the present value method. The objective is minimization of the expected present value of costs over the time horizon. The numerical example and a sensitivity analysis are provided to analyze the effect of changes in the values of the different parameters on the optimal solution. http://www.ijsom.com/article_2661_e100d76224650bd408ea58ca1ab29758.pdf 2016-05-01 1192 1214 10.22034/2016.1.06 Supply chain Inventory management Markovian Costs Deteriorating Items Mehri Nasrabadi nasrabadi.mehri1392@gmail.com 1 Department of Industerial Engineering, Kharazmi University, Tehran, Iran AUTHOR Abolfazl Mirzazadeh a.mirzazadeh@aut.ac.ir 2 Department of Industerial Engineering, Kharazmi University, Tehran, Iran LEAD_AUTHOR Aggarwal, S.P. and Jaggi, C.K. (1995). Ordering policies of deteriorating items under permissible delay in payments, Journal of the Operational Research Society, Vol.46, pp. 658-662. 1 Alizadeh et al, (2011). 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ORIGINAL_ARTICLE Modeling the Hybrid Flow Shop Scheduling Problem Followed by an Assembly Stage Considering Aging Effects and Preventive Maintenance Activities Scheduling problem for the hybrid flow shop scheduling problem (HFSP) followed by an assembly stage considering aging effects additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at the same time. The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan). A mathematical modeling is presented and its validation is shown by solving an example in small scale. Since this problem has been proved strongly NP-hard, in order to solve the problem in medium and large scale, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms. http://www.ijsom.com/article_2669_40f535377d1bc0b0f758753062e5056e.pdf 2016-05-01 1215 1233 10.22034/2016.1.07 Scheduling Hybrid flow shop Assembly Aging effects Preventive maintenance activities Seyyed Mohammad Hassan Hosseini sh.hosseini51@gmail.com 1 Industrial Engineering and Management Department, Shahrood University of Thechnology, Shahrood, Iran LEAD_AUTHOR A. Allahverdi, FS.Al-Anzi. (2009) The two-stage assembly scheduling problem to minimize total completion time with setup times. Computers & Operations Research. Vol. 36, pp. 2740-2747. 1 A. Bachman, A. Janiak. 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(2003) Powerful heuristics to minimize makespan in fixed, 3-machine, assembly-type flow shop scheduling. European Journal of Operational Research. Vol. 146, pp. 498-516. 7 Ch. Koulamas, GJ. Kyparisis. (2001) The three-stage assembly flow shop scheduling problem. Computers & Operations Research, Vol. 28,  pp. 689-704. 8 CN. Potts, SV. Sevast'Janov, VA. Strusevich, LN. Van Wassenhove, CM. Zwaneveld. (1995) The two-stage assembly scheduling problem: Complexity and approximation. Operations Research. Vol. 43, pp. 346-355.  9 CY. Lee, TCE. Cheng, BMT. Lin. (1993) Minimizing the makespan in the 3-machine assembly-type flowshop scheduling problem. Management Science, Vol. 39, pp. 616-25. 10 D. Quadt, H. Kuhn. (2007) A taxonomy of flexible flow line scheduling procedures. European Journal of Operational Research. Vol. 178, pp. 686-698. 11 D. Yang, TCE. Cheng, S. Yang, Ch. Hsu. (2012) Unrelated parallel-machine scheduling with aging effects and multi-maintenance activities. Computers & Operations Research. Vol. 39, pp. 1458-1464. 12 FS. Al-Anzi, A. Allahverdi, (2009) Heuristics for a two-stage assembly flow shop with bicriteria of maximum lateness and makespan. Computers & Operations Research. Vol. 36, pp. 2682-2689. 13 G. Mosheiov. (2001) Parallel machine scheduling with a learning effect. Operational Research Society. Vol. 52, pp. 1165-1169. 14 G. Schmidt. (2000) Scheduling with limited machine availability, European Journal of Operational Research. Vol. 121, pp. 1-15. 15 H. Chou-Jung Hsu. (2013) Single-Machine Scheduling with Aging Effects and Optional Maintenance Activity Considerations. Mathematical Problems in Engineering. DOI: 10.1155/2013/634503. 16 H. Mokhtari, M. Dadgar. (2015) A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing. International Journal of Supply and Operations Management. Vol. 2(3), pp. 871-887. 17 J. Blazewicz, K. EckeK, E. Pesch, G. Schmidt, J. Weglarz. Handbook on Scheduling from Theory to Application. Springer, USA, 2007. 18 M. Elbounjimi, G. Abdul-Nour, D. Ait-Kadi. (2015) A collocation-based approach to designing remanufacturing closed–loop supply chain network. International Journal of Supply and Operations Management. Vol. 2(3), pp. 820-832. 19 M. Yokoyama. (2001) Hybrid flow-shop scheduling with assembly operations. International Journal of Production Economics. Vol. 73, pp. 103-116. 20 M. Yokoyama, DL. Santos. (2005) Three-stage flow-shop scheduling with assembly operations to minimize the weighted sum of product completion times. European Journal of Operational Research. Vol. 161, pp. 754-770. 21 ML. Pinedo. Scheduling Theory, Algorithms, and Systems. Third Edition. Springer, USA, 2008. 22 TCE. Cheng, G. Wang. (1999) Scheduling the fabrication and assembly of components in a two-machine flow shop. IIE Transactions. Vol. 31, pp. 135-143. 23 P. Fattahi, SMH. Hosseini, F. Jolai, R. Tavakoli-Moghadam. (2014) A branch and bound algorithm for hybrid flow shop scheduling 4 problem with setup time and assembly operations. Applied Mathematical Modelling. Vol. 38, pp. 119-134. 24 P. Fattahi, SMH. Hosseini, F. Jolai. (2013) A mathematical model and extension algorithm for assembly flexible flow shop scheduling problem. International journal of advanced manufacturing technology. Vol. 65, pp. 787–802. 25 R. Ruiz, JA. Vazquez-Rodriguez. (2010) Invited Review The hybrid flow shop scheduling problem. European Journal of Operational Research. Vol. 205, pp. 1-18. 26 T.C.E. Cheng, O. Ding, B.M.T. Lin. (2004) A concise survey of scheduling with time-dependent processing times. European Journal of Operational Research. Vol. 152, pp. 1-13. 27 Y. Ma, C. Chu, C. Zuo A survey of scheduling with deterministic machine availability constraints. Computers & Industrial Engineering 28