IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2860 10.22034/ijsom.2021.108660.1852 Research Paper Optimal Control for Inventory System Under Uncertainty on Demand and Delivery Using Robust Linear Quadratic Control Approach Optimal Control for Inventory System Under Uncertainty on Demand and Delivery Using Robust Linear Quadratic Control Approach Sutrisno Sutrisno Department of Mathematics, Faculty of Science and Mathematics, Universitas Diponegoro, Semarang, Indonesia Widowati Widowa Department of Mathematics, Faculty of Science and Mathematics, Universitas Diponegoro, Semarang, Indonesia Tjahjana Redemtus Department of Mathematics, Faculty of Science and Mathematics, Universitas Diponegoro, Semarang, Indonesia 01 02 2022 9 1 1 14 18 09 2020 11 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2860.html

The supply chain management comprises many uncertain parameters such as the demand value and delivered product rate as the result of an imperfect delivery process. In this article, therefore, a mathematical model in a linear dynamical state-space equation is formulated for an inventory system with uncertain demand value and imperfect delivery process developed from the existing classical model. The new model is used to determine the optimal decision for this inventory system i.e. to calculate the optimal amount of product that should be ordered from the supplier. Moreover, the optimal decision is calculated for the purpose to control the inventory level as the decision-maker wanted to, in this paper, the inventory level is brought to a set point. The robust linear quadratic control, which is an existing model, is employed to this system with a numerical experiment performed to illustrate the controlling responses. From the obtained results, it achieved the optimal decision with the proper control of the inventory level based on the performed set-point control problem. In addition, the performed computational experiment is compared to some related existing works. The analysis showed that the achieved optimal decision is well enough and is not worse than the other results. In conclusion, the proposed model and the method performed in this research are implementable and therefore can be used by practitioners especially in the supply chain management field.

Optimal control robust LQR uncertain delivery uncertain demand
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2861 10.22034/ijsom.2021.109063.2160 GOL20 Integration of New Business Models in Smart Logistics Zones Integration of New Business Models in Smart Logistics Zones Schmidtke Niels Otto von Guericke University, Institute of Logistics and Material Handling Systems, Magdeburg, Germany Behrendt Fabian University of Applied Science Magdeburg-Stendal, Stendal, Germany Gerpott Falk Fraunhofer Institute for Factory Operation and Automation IFF, Magdeburg, Germany Wagner Margarete Fraunhofer Institute for Factory Operation and Automation IFF, Magdeburg, Germany 01 02 2022 9 1 15 33 15 04 2021 06 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2861.html

This paper is dedicated to the core challenge of sustainably integrating new and viable business models into logistics systems in the context of the digital transformation. On the one hand, enterprises are facing increased competitive pressure and growth gaps in their own product portfolio; on the other hand, new technology and system solutions are finding their way into enterprises. These new solutions lead to significant changes in the cost structure as well as in the process design. Especially in increasingly digitalised and automated economic sectors such as logistics, production or processing industries, the adaptation and development of the own business model requires a systematic approach that presupposes the use and integration of proven methods. In the context of designing Smart Logistics Zones the interaction of logistical objects, processes, systems and the physical and digital infrastructure is achieved in a goal-oriented manner, depending on the requierements and the situation. An interactive design of the future of human-technology organization takes places. The procedure of the Smart Logistics Zone should support entrepreneurial decision processes purposefully and on the core idea of an Industrie 4.0 in preliminary way. In addition to the inte-grative research concept, this paper focuses on the application of the methodological approach to a reference scenar-io of the Smart Logistics Zone and an exemplary business model.

smart logistics zone digital transformation logistics 4.0 IoT business model business model innovation
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2862 10.22034/ijsom.2021.108651.1843 Research Paper Multi-objective Optimization of Multi-mode Resource-constrained Project Selection and Scheduling Problem Considering Resource Leveling and Time-varying Resource Usage Multi-objective Optimization of Multi-mode Resource-constrained Project Selection and Scheduling Problem Considering Resource Leveling and Time-varying Resource Usage Davari Ardakani Hamed Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran Dehghani Ali Department of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran 01 02 2022 9 1 34 55 10 09 2020 07 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2862.html

In this paper, a multi-objective mixed-integer programming model is developed to cope with the multi-mode resource-constrained project selection and scheduling problem, aiming to minimize the makespan, maximize the net present value of project cash flows, and minimize the fluctuation of renewable resource consumption between consecutive time periods. Moreover, activities are considered to be subject to generalized finish-to-start precedence relations, and time-varying resource usage between consecutive time periods. To assess the performance of the proposed model, 30 different-sized numerical examples are solved using goal programming, epsilon constraint, and augmented epsilon constraint methods. Afterward, Tukey test is used to statistically compare the solution methods. Moreover, VIKOR method is used to make an overall assessment of the solution methods. Statistical comparisons show that there is a significant difference between the mean of the resource leveling objective functions for all the solution methods. In other words, goal programming statistically outperforms other solution methods in terms of the resource leveling objective function. This is not the case for the other objective functions and CPU times. In addition, results of the VIKOR method indicate that the goal programming method outperforms the other solution methods. Hence, goal programming method is used to perform some sensitivity analyses with respect to the main parameters of the problem. Results show that by improving any of the parameters at least one objective function improves. However, due to the conflicting nature and the impact of weights of objective functions, in most cases, the trend are not constant to describe a general pattern.

Project Portfolio Selection Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) Multi-objective optimization Resource Leveling Time-Varying Resource Consumption Time Value of Money
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2864 10.22034/ijsom.2021.109227.2261 Case Study Risks in the Automotive Industry Supply Chain Risks in the Automotive Industry Supply Chain Cano-Olivos Patricia Logistics and Supply Chain Management, UPAEP, Puebla, Mexico Sosa-Gallardo Jorge-Fernando Logistics and Supply Chain Management, UPAEP, Puebla, Mexico Sánchez-Partida Diana Logistics and Supply Chain Management, UPAEP, Puebla, Mexico Martínez-Flores José-Luis Logistics and Supply Chain Management, UPAEP, Puebla, Mexico 01 02 2022 9 1 56 79 12 07 2021 06 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2864.html

This paper presents an action plan which to minimize the supply chain disruptions of trade automotive in Mexico. This research was carried out basically in 5 steps: (a) to apply surveys to suppliers of the automotive industry for (b) identifying and classifying the risk factors in the automotive supply chain. (c) Subsequently to evaluate them through the AHP (d) so that from the principle of Pareto, risk factors are prioritized and (e) finally, design an action plan to minimize or eliminate the risk factors that disrupt supply chain operations. The research finds the critical factors that jeopardize the excellent performance of the chain of supply of the automotive industry. Structured plans do not exempt supply chains from the possibility of risk. However, it helps enterprises prepare them much better to deal with risk, especially in changing, complex, global, and volatile. Risk management is vital in the excellent performance of an organization, and it is advisable to have protection mechanisms. That is part of a structured plan based on a rigorous understanding of the vulnerable points of the extended chain and the application of containment schemes and mitigation in the proper combination of redundancy and flexibility.

SCM performance Planning Supply Chain disruptions
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2863 10.22034/ijsom.2021.108087.1537 Research Paper Bi-Objective Model for Ambulance Routing for Disaster Response by Considering Priority of Patients Bi-Objective Model for Ambulance Routing for Disaster Response by Considering Priority of Patients Talebi Ehsan College of Engineering, University of Tehran, Tehran, Iran Shaabani Mahnaz Industrial Engineering, Khatam University,Tehran, Iran Rabbani Masoud College of Engineering, University of Tehran, Tehran, Iran 01 02 2022 9 1 80 94 26 07 2019 07 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2863.html

Disaster situation could suddenly apply large number of injured people and disarrange the emergency medical service simultaneously (EMS). Using all facilities, ambulance, rescue helicopter and medical drone as integrated part and making decision for assigning to patient’s efficiency are concerns of EMS. therefore, in this study we introduce a new bi-objective model for EMS in order to reduce the rate of mobility and mortality with aim of reducing latest service completion time and total cost of system simultaneously. By recognition level of injury, we consider two types of patients: i. red code patients who have been injured seriously and have to be taken to an hospital. and ii. green code patients who are injured slightly and are treated at the same place. Since making decision and responding to disaster situation should be with high quality within seconds, for this purpose after validating and solving that by augmented ε-constraint method by GAMS, we applied two NSGA-II and customized Bees algorithm for multi objective solution that called Multi Objective Bees Algorithm (MOBA) in dynamics and uncertain situation for coping high frequency within very short response time and near the optimum solution result. The quality of the result is considered for choosing the metaheuristic solution. At the end, sensitive analysis is implemented on the model and the effect of reducing and increasing some of parameters on the model is investigated.

Ambulance Routing Disaster Response Emergency Medical Service NSGAII Multi Objective Bees Algorithm
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2865 10.22034/ijsom.2021.108817.1968 Research Paper Inventory Policies for Non-instantaneous Deteriorating Items with Advance sales, Advertisement efforts and effect of Static Versus Dynamic Rebate Inventory Policies for Non-instantaneous Deteriorating Items with Advance sales, Advertisement efforts and effect of Static Versus Dynamic Rebate Shah Nita Department of Mathematics, Gujarat University, Ahmedabad, India Shah Pratik .U.Shah Government Polytechnic College, Surendranagar, India Patel Milan Department of Mathematics, Gujarat University, Ahmedabad, India 01 02 2022 9 1 95 107 14 12 2020 22 12 2021 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2865.html

This paper presents study about the effects of rebates on an inventory model for non- instantaneous deteriorating items with preservation technology investments. Demand of the product is considered to be price-sensitive as well as affected by advertising efforts, advanced booking price discounts and rebates on price once deterioration starts. In the study, a three-phase model has been developed. The first phase is the production phase together with advance booking of the product at a discounted selling price. Second phase is the sales phase at a normal selling price and there is no deterioration of products in this phase. In the third phase products start deteriorating hence a price rebate is offered to the customers on purchase of the product. Effects of static versus dynamic rebates are studied. Aim of the paper is to obtain optimum cycle time, ordering quantity, selling price, amount of advertisement expenditures and amount of preservation expenditures in order to maximize total profit of the retailer. It is observed from the study that offering rebates in the deterioration phase helps retailers to increase demand that results to increase in total profit. By preservation technology investments retailers can reduce deterioration rate and hence he can generate more revenue.

Inventory Deterioration Advertisement Advance booking Rebate Preservation
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2870 10.22034/ijsom.2021.109031.2138 GOL20 Multi-echelon Inventory System Selection: Case of Distribution Systems Multi-echelon Inventory System Selection: Case of Distribution Systems Sbai Noucaiba Department of Industrial Engineering Mohammed V University, Rabat, Morocco Benabbou Loubna Departement of Management Sciences, University of Quebec at Rimouski, Lévis, Québec, Canada Berrado Abdelaziz Department of Industrial Engineering Mohammed V University, Rabat, Morocco 01 02 2022 9 1 108 125 05 04 2021 09 02 2022 Copyright © 2022, Kharazmi University. 2022 http://www.ijsom.com/article_2870.html

Inventory management presents numerous challenges for many supply chains as they are becoming more complex and composed of multiple stages. Using appropriate multi-echelon inventory management policies allows supply chains to deliver the required level of responsiveness efficiently by optimizing inventory levels across the entire network and improving customer service levels. This paper provides a Multi-Criteria Decision Making (MCDM) approach for the multi-echelon inventory system selection problem. The scope of this paper is limited to the case of Distribution systems. The suggested approach identifies for a given supply chain configuration, a set of selection criteria related to supply chain costs and overall responsiveness. These criteria are used to compare and choose the best alternative from different multi-echelon distribution inventory system configurations by using a suitable MCDM method. Eight different multi-echelon distribution inventory system alternatives are generated. Each one is a combination of three main inventory policies: (i) replenishment policies, (ii) ordering policies, and (iii) safety stock allocation policies. The suggested approach is illustrated in the case of the pharmaceuticals products supply chain in the public sector in Morocco. Depending on the decision problem nature and other criteria, the AHP method proved to be the suitable MCDM method for selecting the best multi-echelon inventory system for the Moroccan pharmaceutical products supply chain. The analysis indicates that assigning inventory to the most downstream facilities close to patients and adopting an installation stock ordering policy implemented by a decentralized decision system is the best option for the supply chain considered in the case study.

Supply Chain Management Multi-echelon inventory management Distribution systems Multi-Criteria Decision Making Pharmaceutical products supply chain
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