@article { author = {Ehtesham Rasi, Reza and Abbasi, Rahele and Hatami, Danial}, title = {The Effect of Supply Chain Agility Based on Supplier Innovation‎ and Environmental Uncertainty}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {94-109}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.1}, abstract = {Today, the continuity of companies is directly related to the ability of companies to enhance competitiveness which the supply ‎chain agility ‎plays an important role in this regard. This study was conducted by ‎the purpose of determining the effect of supplier ‎innovation and environmental uncertainty on supply ‎chain agility with the mediating role of information ‎sharing, strategic resourcing, supply chain orientation and ‎market orientation in Parts suppliers of Sazeh Gostar ‎Saipa Company. The present research is applied in terms of its purpose and is descriptive-survey in terms of method, which the statistical population consisted of 515 ‎managers of Parts suppliers of Sazeh Gostar Saipa ‎Company. Accordingly, the Cochran formula was used to determine ‎the number of samples, a total of 228 ‎managers participated in this study. Standard ‎questionnaires were used to sample. Correlation test ‎results showed that there is a significant positive ‎relationship between the research variables (p<0.01). Also, ‎the results of structural equation modeling showed that ‎the model presented in this study has a suitable fit and the ‎set of factors that influenced the supply ‎chain agility ‎in this model can explain 98% of the changes ‎in supply chain agility (R2=0.98).‎}, keywords = {Innovation,Uncertainty,Agility,Information,Strategic,‎Supply chain orientation}, url = {http://www.ijsom.com/article_2781.html}, eprint = {http://www.ijsom.com/article_2781_e74b41f6b1ed76fcafaa9a1ed0bee6fa.pdf} } @article { author = {Hoseini, Seyed Mehran and Mollaverdi, Naser and Hejazi, S. Reza and Rezvan, Mohammad Taghi}, title = {A Multi-attribute Approach for Simultaneous Determination of Preventive Replacement Times and Order Quantity of Spare Parts}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {110-125}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.2}, abstract = {One of the most important activities in preventive maintenance is replacement of spare parts prior to failure. The aim of this paper is to propose an approach which determines jointly the preventive replacement interval and the spare parts inventory by considering different criteria and interacting with decision makers. In this approach, preventive replacement intervals, determined by experts of production and maintenance, are ranked by analytical hierarchy process (AHP). Criteria such as cost per unit of time, availability, remaining lifetime, and reliability are used. Then, a mixed integer nonlinear multi-objective model presented that it simultaneously specifies the period of preventive replacement and the required number of spare parts. This model considers the mentioned criteria and the inventory control costs of spare parts as different objective functions. Since, the solution of the problem depends on the decision maker’s strategy, it need interact with the decision-makers and consequently the proposed model could be solved using goal programming approach. The applicability of the proposed approach is illustrated by two numerical examples. The effect of key parameters on the optimal decisions is investigated for two examples.}, keywords = {Preventive replacement,Spare parts,Analytical hierarchy process (AHP),Goal programming}, url = {http://www.ijsom.com/article_2782.html}, eprint = {http://www.ijsom.com/article_2782_1ce09cad2ab5c14aa13d454d106924e0.pdf} } @article { author = {Žilionienė, Daiva and D&#039;Acierno, Luca and Botte, Marilisa and Gallo, Mariano}, title = {A General Methodology for Reducing Computing Times of Road Network Design Algorithms}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {126-141}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.3}, abstract = {In this paper a general methodology is proposed for reducing computing times in procedures for solving RNDPs. Extensively studied in the literature, such problems concern the design of road networks, in terms of flow directions, capacity expansion and signal settings in urban contexts, and in terms of link addition and capacity expansion in rural contexts. The solution is almost always formulated as a bi-level model, where the upper level operates on the network design decision variables, while the lower level estimates the equilibrium traffic flows, which must be known in order to determine objective function values. Computing times required for calculating equilibrium traffic flows at each iteration of the network design procedure significantly affect the total solution time. Hence, any reduction in computing times of the lower level, which has to be implemented numerous times at any step of the upper-level algorithm, allows the global computing time to be considerably reduced. In this context, the methodology proposed herein seeks to reduce computing times of the traffic assignment problem and hence of the whole network design procedure, acting on the traffic flows adopted in the initialisation phase of the assignment algorithm. The proposed approach is tested on a real-scale case study: the rural road network of Vilnius County (Lithuania). Preliminary results underline the feasibility of the proposal and a significant reduction in computing times of up to 80% compared to traditional assignment approaches.}, keywords = {Road network design problem,Bi-level optimization model,Rural road network analysis,Road capacity expansion,Computing times reduction}, url = {http://www.ijsom.com/article_2783.html}, eprint = {http://www.ijsom.com/article_2783_50cbe57201370d9e263c0ac8e48f59ae.pdf} } @article { author = {shirmohammadi, Hamid and Hadadi, Farhad}, title = {Optimizing Total Delay and Average Queue Length Based on Fuzzy Logic Controller in Urban Intersections}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {142-158}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.4}, abstract = {Currently, traffic congestion has become a serious problem in most developed cities. It is caused by an increasing number of the vehicles and the delay on arterial roads resulting in negative consequences regarding air quality, travel time, and travel safety. To reduce the traffic volume and congestion, recent solutions offer optimization of operational characteristics including the total delay and average queue length in urban intersections. Optimizing such characteristics are considered as the major breakthrough concepts of applying artificial intelligence in transportation engineering. Accordingly, the aim of this study was to develop and apply the fuzzy controller to reduce the total delay and average queue length in urban intersections. To this end, effective variables like the total delay and average queue length were simulated using the fuzzy logic controller. Then, the results were graphically simulated for the experts. Furthermore, the total delay and average queue length were compared employing the fixed-time control and fuzzy controller systems. The results indicated that in fuzzy controller system rather than the fixed-time control system, the delay and average queue length were remarkably optimized. Statistical tests also approved the efficiency of the fuzzy controller as an optimum controller system as compared to the fixed controller system. The findings of this study may help the traffic engineers and urban managers to control the traffic congestion issues based on predicting and optimizing the delay and queue length and increasing the road safety in urban intersections in the future.}, keywords = {Traffic congestion,Total delay,Average queue length,Fixed-time controller,Fuzzy logic controller,Optimum classification}, url = {http://www.ijsom.com/article_2784.html}, eprint = {http://www.ijsom.com/article_2784_ee855b241160915cfeaf50d7b6776453.pdf} } @article { author = {Bicakci, Papatya Sevgin and Kara, İmdat}, title = {A New Formulation for the Single Machine Order Acceptance and Scheduling Problem with Sequence-Dependent Setup Times}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {159-167}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.5}, abstract = {Order acceptance and scheduling problem consists of simultaneously deciding which orders to be selected and how to schedule these selected orders. An extension of this problem was introduced by Oğuz, Salman & Bilgintürk in 2010 and a mathematical formulation was presented. They defined the problem with sequence-dependent setup times and release dates. In this paper, we consider the case where there are no release dates for all orders. We develop a new mathematical formulation with O(n2) binary variables and O(n2) constraints and conduct a detailed computational analysis with CPLEX 12.4 by solving benchmark instances proposed by Cesaret, Oğuz, & Salman (2012). Reduced formulation of Oğuz, Salman & Bilgintürk (2010) can solve the test problems up to 10 orders to optimality in given time limit. Our proposed formulation can solve all the available instances up to 100 orders to optimality within the same time limit. We observe that our formulation is extremely faster than the existing one and can solve small and moderate size real-life problems to optimality.}, keywords = {Order acceptance,Single machine scheduling,Mathematical formulation,Order rejection,Sequence dependent setup times}, url = {http://www.ijsom.com/article_2786.html}, eprint = {http://www.ijsom.com/article_2786_26edf0ae892012e24fda3b05edf255bd.pdf} } @article { author = {Hosseini, Zahra sadat and Fallah Nezhad, Mohammad saber}, title = {Developing an Optimal Policy for Green Supplier Selection and Order Allocation Using Dynamic Programming}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {168-181}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.6}, abstract = {Supplier selection is one of the critical issues in the supply chain. Green supplier selection is performed based on the assessment of quantitative and qualitative criteria in two fields, including economic, environmental attributes. In this study, a two-level supply chain model has been proposed for green supplier selection and order allocation in a multi-period and single-product environment. In the first phase, the analytic hierarchical process (AHP) method is used to rank the suppliers and in the second phase, a model is designed based on constraints such as demand, capacity, and allowed level of inventory and shortage to maximize the total value of purchase (TVP) and total profit of purchase (TPP). Demand is assumed to be stochastic in different periods. Thus random demand leads to create the various scenarios in the planning horizon. A new integrated approach is presented based on stochastic programming and dynamic programming to solve the problem. The incorporation of stochastic demand condition and application of dynamic programming is a novel idea. Finally, a Numerical example is provided to investigate the procedure in details.}, keywords = {Green supplier selection,Order allocation,Dynamic programming,Stochastic programming}, url = {http://www.ijsom.com/article_2787.html}, eprint = {http://www.ijsom.com/article_2787_ceab87f694a4c3c89379f735e4910c35.pdf} } @article { author = {Udoh, Ben and Prince, Abner and Udo, Emmanuel and Kelvin-Iioafu, Lovlyn}, title = {Insecurity on Economic and Business Climate; Empirical Evidence from Nigeria}, journal = {International Journal of Supply and Operations Management}, volume = {6}, number = {2}, pages = {182-187}, year = {2019}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/2019.2.7}, abstract = {Insecurity undermines the economic and business prowess of a nation. Tallying to the human cost, it sabotaged the right to life, liberty, and freedom. This study tests the long run effect and cause of insecurity from 2007-2017 in Nigeria. Using a framework of the Auto-Regressive Distributed Lag Model (ARDL) and Error Correction Model (ECM). Findings revealed that insecurity in Nigeria is majorly internal factors and government expenditure on security in Nigeria is far below the United Nations Standard. The ECM report that disequilibrium caused by internal factors instigating insecurity can be revised back to equilibrium at 25% annually. To improve the economic and business climate competitive advantage.}, keywords = {ARDL,ECM,Insecurity,Economic,Business climate}, url = {http://www.ijsom.com/article_2785.html}, eprint = {http://www.ijsom.com/article_2785_a16a5b4d6ea9aa3fb5d6ad84184d1891.pdf} }