The hybrid vehicle routing problem is an extension of the green vehicle routing problem where vehicles can use different fuels. In this research, a bi-objective hybrid vehicles routing problem is presented and solved bu considering alternative paths, various lengths and reliabilities. The first objective function minimizes overall system costs and fuel consumption and greenhouse gas emissions, whereas the second objective function maximizes the reliability of the entire system with alternative paths and several reliabilites. The proposed model is formulated as mixed-integer nonlinear programming and a bi-objective simulated annealing (MOSA) algorithm along with the e-constraint method is used as solution strategy. The implementation of the proposed method is presented using some numerical instances.

Operating rooms (OR) are one of the most expensive parts of a hospital with complex processes, and the efficient use of resources is of utmost importance. Therefore, proper management and operation of operating rooms are extremely crucial. OR scheduling ensures that the surgeries are performed at the proper time, patients are treated effectively and safely, resources are used effectively, and staff is increased in work efficiency. Furthermore, accurately scheduled surgeries are safer for patients' healing processes. This is dependent on factors such as the availability of qualified personnel at the appropriate time, the readiness of surgical equipment, and the provision of proper sterilization and hygienic conditions. Surgical team scheduling ensures that surgeries begin on time, are completed effectively, and patients are treated safely. It is also critical to reduce employee fatigue and balance the workload. As a result, integrating surgical teams into operating room scheduling problems provides significant benefits. Accordingly, 29 research articles focusing on the problem of OR scheduling, within the scope of constraints on surgical team members, scheduling strategies, uncertainties, and solution methods, are thoroughly reviewed in this study.

This paper focuses on modelling inelasticity of additively manufactured polylactide (PLA) thermoplastic using Fused Deposition Modelling (FDM) printing technology. The material response of PLA is viscoplastic and temperature-dependent, as is typically seen for thermoplastics. The inelastic deformation of printed PLA undergoes initial yielding, strain softening, and subsequent failure. The Three-Network (TN) constitutive model was employed in this work, which captures experimentally observed material response and consists of three molecular equilibrium and time-dependent viscous networks that act in parallel. The parameter identification was performed in accordance with experimental data from uniaxial testing and a validation experiment was carried out by loading plate with a hole and measuring its strain distribution using Digital Image Correlation (DIC) method, which was compared with the predictions from Finite Element Analysis (FEA).

The study of the stress state and power parameters when pulling workpieces in a special die with an inclined working surface at various shapes of the plastic deformation zone and geometric parameters of the special die was conducted. The distinctive feature of the proposed special die and the metal treatment process in the working channel of this die was described. The theoretical provisions and assumptions from the fundamental theory of plasticity and metal forming were used. The influence of the intensity of shear deformations on the stress state and force at the angles of inclination of the working surface of the die within 45–20°, the value of the ratio of the diameter of the workpiece to the length of the inclined surface d/z=1.5–2.0 was investigated. The optimal d/z ratio was determined by the method to a rigid punch indenting a rigid-plastic half-space, as well as by the method of strain energy. The field of slip lines and hodographs of velocities for various shapes of the deformation zone and geometric parameters of a special die were constructed. Based on the constructed slip line fields and velocity hodographs, the mean stress and stress components at the nodal points of the slip line field with the compilation of the equilibrium equations for all forces applied to the plastic zone were calculated. The study of the influence of contact friction between the working surface of the die channel and the workpiece on the stress state and power parameters during pulling was carried out. It was revealed that the optimal ratio d/z=1.5 and the optimal angle of inclination of the working channel of the die α=20°. It was found that for these parameters in the zone of plastic deformation, mainly significant compressive stresses act, which favorably affect the obtaining of a homogeneous and refined microstructure, and also exclude the appearance of anisotropy due to the implementation of maximum shear deformations in the workpiece.

Agricultural food supply chains of different grains such as wheat, rice, and corn include several processes from cropping and harvesting to distribution. Integrating these processes to reduce costs, in addition to providing sufficient supply, are of the major goals of agri-food supply chain management. Rice is an important grain that constitutes an important part of people’s diets throughout the world. FAO predicts that global rice utilization would increase over the next few years. Considering rice's importance, in this paper, a mixed-integer linear mathematical model for designing and planning of rice supply chain is proposed which aims to maximize total profit by integrating different decisions of the rice supply chain including supplier selection, cropping, fertilizing, pest control, harvesting, milling, transportation, and distribution. This model considers different rice varieties and takes into account irrigation water requirements of crops and available water resources. A case study of Iran farmlands in Gilan province is employed to show the applicability and advantages of the proposed model for the rice supply chain. Results indicate that increasing conversion ratio of paddy to rice and reducing labor costs would have a significant impact on the total profit of the supply chain.

Current optimization strategies are based on the increase the productivity and the quality with lower cost in short time. Grey relational analysis “GRA” based on Taguchi design was proposed in this paper for simultaneous improvement of surface quality and productivity. The turning trials based on mixed Taguchi L18 factorial plan were conducted under dry cutting conditions for the machining couple: AISI D3 steel/mixed ceramic inserts (CC650). The machining parameters taken into account during this study are as follow: major cutting edge angle (χr), cutting insert nose radius (r), cutting speed (Vc), feed rate (f), and depth of cut (ap). Significant effects of machining parameters and their interactions were evaluated by the analysis of variance. Through this analysis, it have been found clearly that feed rate and cutting insert nose radius had a big significant effects on surface quality while depth of cut, feed rate followed by cutting speed had a major effect on productivity. The mathematical relationship between the machining parameters and the performance characteristics was formulated by using a linear regression model with interactions. Optimal levels of parametric combination for achieving the higher surface quality with maximum productivity were selected by grey relational analysis which is based on the high value of grey relational grade. Confirmation experiments were carried out to prove the powerful improvement of experimental results and to validate the effectiveness of the multi-optimization technique applied in this paper.

In this research, crash test results from CNG locating method optimization approach for crashworthiness and testing its safety are presented. The locating process is based on principal energy considerations inspired from the current design process in passenger vehicle design development. The potential of the vehicle concept to absorb kinetic energy can be estimated at the very beginning of the design process by the free crash lengths in the different areas of the vehicle and estimates of average forces required in the specific segment and parts of the car body at particular crash phases. Based on the basic principle of vehicle crash analysis using the finite element method, a passenger VAN finite element model was selected to simulate the front and side rear collision test of the VAN, therefore the LS-DYNA software is adopted to calculate the deformation of the car and the acceleration time history curves during the crashing process; the anti-impact capability of the vehicle is evaluated from this simulation. It is important to determine appropriate force distributions and the corresponding loads paths through the whole structure for all relevant crash load in dedicated crash test cases. The results demonstrate that the improvement of local structure and location for the required CNG tanks in safe locations in vehicle chassis can promote the crashworthiness of the car, but the further improvement needs a major change of the vehicle structure. The outcomes are interpreted by using LS-PREPOST to analyze the energy absorption characteristics during crash for different cases at a velocity of 50km/h the duration of 12ms. The result analysis was necessary to derive distinct deformation phases characteristic and following that, the essential crash elements are compared with and without CNG tanks installation in each crash case. At last, the conclusion determines the proposed tank locating model in the selected passenger VAN is within the safe range of crash analysis standards.

Globalization and increasing competition in global markets have forced businesses to provide a high level of service to their customers. Time-sensitive transportation systems which are used in transportation of perishable goods, express mail delivery, and emergency services are playing a very important role in this regard. This paper addresses the problem of uncapacitated multiple allocation p-hub center problem (UMApHCP) which is fundamental in proper functioning of time-sensitive transportation systems. A mixed-integer programming formulation is proposed for the problem and a highly efficient Benders decomposition algorithm is developed for solving it. The proposed algorithm is capable of solving large-scale instances of the problem to optimality in order of seconds.

Forecasting stock index has been received great interest because an accurate prediction of stock index may yield benefits and profits for investors, economists and practitioners. The objective of this study is to develop two efficient forecasting models and compare their performances in one day-ahead forecasting the daily Vietnamese stock index. The model development used the data across 9 years of the trading days. The developed models are based on two artificial intelligence techniques, including adaptive network based fuzzy inference system (ANFIS) and long short-term memory (LSTM). The performance indexes including RMSE, MAPE, MAE and R were used to make comparison of the models. The experimental results reveal that both models successfully forecasted the daily Vietnamese stock index with a high accuracy rate. The comparative results of the two models were then discussed and analyzed. It was found that the LSTM model outperformed the hierarchical ANFIS model in forecasting stock index of the Vietnamese stock market.

Poor urban planning and traffic congestion lead to excessive delays in workers’ transit times and decrease their quality of life, especially in emerging countries. Several medium and large companies have a need to hire a transport service for their staff. In this type of transportation system, there is a heterogeneous fleet of vehicles, which are assigned to a set of predefined routes. However, the total transport delay can be even greater if the private transportation system is inefficient or not controlled. The approach proposed in this study seeks to optimize the private transport service by defining the best allocation of its fleet to its routes. A mathematical model is proposed to minimize user wait times. This approach is validated using real data obtained from a transport company in Co-lombia. The results demonstrate the quantitative benefits that can be achieved when the proposed approach is implemented, represented by a considerable reduction in user wait times.