Recently, there has been an increase in the use of laser beam welding of mild steel in various industries, including petroleum refineries, power plants, pharmaceuticals, and even residential areas. This research paper focuses on studying the effects of laser welding process parameters, such as laser power and welding speed, on the tensile strength of welds. To do this, three types of laser beam oscillations (sinusoidal path, triangular path, and square path) were performed to weld 125mm x 60 and 1.8 thick sheets of ASTM A36 mild steel alloy. The researchers used statistical tools such as ANOVA to generate mathematical models and experimental designs using the Taguchi method. The results indicate that the optimal welded joint has good mechanical properties after laser welding. For ASTM A36 mild steel, the optimal parameters for laser welding are a laser power of 1800 W, a welding speed of 50 mm/s, and triangular welding mode.

Amongst various structures, 2D panels are widely used in many industries and in each application, there are many ambient vibrations which can be converted into electrical energy. The very efficient method to utilize can be using piezoelectric patches which are stuffiest enough for various applications like energy harvesting. This study presents a novel approach for investigating energy harvesting in smart structures using composite panels integrated with piezoelectric patches. The panels are chosen to symmetry-balanced laminated composites, and modal and harmonic analysis conducted using the Rayleigh-Ritz method. To compute the kinetic and potential energy components of the piezoelectric patches at a local level, piecewise Heaviside functions are employed, and these energy components are integrated into the equations of motion together with those of the host composite plate. The results of the numerical method are validated by a commercial finite element software (FEM) COMSOL and there is a good match between FEM and this paper results. By subjecting the laminated composite with piezoelectric patches to forced vibration while varying the lamination parameter, the power output is optimized. The findings emphasize the substantial impact of the lamination parameter on power output, indicating that modifications can result in significant power output increase.

Proficient routes were devised for coupling different aromatic/aliphatic acids with amines to form amide linkage using various catalysts. Under the optimized reaction conditions, highest conversion was possible without formation of any by-products. All synthesized compounds were purified using column chromatography and characterized by mass spectrometry, nuclear magnetic resonance spectrometry and liquid chromatography-mass spectrometric analysis.

Production managers face the growing trend of rapid-response orders and inevitable production defects and failures; they must carefully measure these factors’ effects to minimize operating expenditures and operational disruption. Inspired by assisting producers decide the optimal runtime policy under these real situations, this work investigates the collective impact of rework, expedited-rate, external source, and machine failures on such a specific fabrication system. A partial outsourcing and expedited manufacturing rate are considered in the studied system to reduce the batch fabricating time. Additionally, defects rework and repair failure machines are implemented to retain the quality and avoid production disruption. Our research scheme consists of (1) developing a model for the mentioned manufacturing characteristics; and (2) analytical and optimization techniques for deciding the best batch runtime decision by minimizing the system’s overall expenses. Lastly, we provide numerical examples to demonstrate the model’s applicability and disclose important, in-depth characteristics that facilitate managerial decision-making.

In this paper a mixed-integer linear programming (MILP) model is developed to be used as a decision support tool for the chemical company Perstorp Oxo AB. The intention with the mathematical model is to maximize the profit and the model can be used in the process of planning the supply chain for the company. Perstorp Oxo is classified as a global company in the process industry and is has production sites in Gent, Castellanza, Stenungsund and Perstorp. The site in Stenungsund is in focus in this paper. The company produces chemicals that later are used for example in textiles, plastic and glass production. Perstorp Oxo also uses inventories in other countries for enabling the selling abroad. It has two larger inventories in Antwerp and in Tees and two smaller in Philadelphia and in Aveiro. The larger facilities store five different products and the smaller take care of one type each. To be able to find feasible and profitable production plans for the company we have developed and implemented rolling horizon techniques for a time horizon of one year and used real sales data. The outcomes from the model show the transportation of products between different production sites, the different production rates, the levels of inventory, setups and purchases from external suppliers. The numerical results are promising and we conclude that a decision support tool based on an optimization model could improve the situation for the planners at Perstorp Oxo AB.

This article examines the possibility of answering the question” can the Arab’s natural gas secure the gas requirements in Europe? “To answer the question, an economic analysis of natural gas was conducted to examine reserve, supply, demand, and international trade first. Second, an economic model to examine distances and transportation costs, for transferring goods from various points of supply to various points of demand, was adopted. The North-West Corner model approach, a QM for Windows-based economic strategy to solve the transportation model problem structure in linear programming, has been used in this regard. Our findings demonstrate that the model is suitable for application since it provides the least distances and the least transportation costs compared to other alternatives. The model estimated that a cost of $309.41 is required to transfer one MMBtu of LNG from origins to final destinations. A decrease of $34.304/MMBtu, 10%, compared to $343.714 /MMBtu. It is concluded that the Arab’s gas could fulfil gas requirements in Europe, and mutual benefit can be accomplished for both parties. European countries will benefit from acquiring new places with less distances and lower delivery costs, and Arab countries would have the chance to get new consumers and play a role in the market given their collective gas reserves and their advantageous strategic locations.

The Medical System of Transportation deals with two online real-time decisions: ambulance dispatching and relocation. Dispatching consists of selecting which ambulance to send to an emergency call; relocation consists of determining how to modify the location of available ambulances in response to changes in the system’s state. Although the literature regarding this problem is extensive, only a limited number of online real-time approaches for ambulance management have been proposed, much less one taking into consideration different types of emergencies and vehicles. This paper proposes an online real-time matheuristic algorithm that combines: i) a new preparedness index defined as the availability probability of a multi-server queue model which is used as an optimization objective and as a control variable for relocation strategies, ii) two mathematical models to solve the relocation problem, one oriented to the maximization of coverage and other to the minimization of the maximum relocation time, and iii) two heuristic algorithms oriented to the maximization of the preparedness level, one to solve the dispatch problem and other to solve the location problem of one ambulance. The computational experiments, based on discrete event simulation and historical data of Bogotá, Colombia, have shown their capability to adequately respond to the necessities of real-time operation.

Data Center energy usage has risen dramatically because of the rapid growth and demand for cloud computing. This excessive energy usage is a challenge from an economic and environmental point. Virtual Machine Placement (VMP) along with virtualization technologies is widely used to manage power utilization in data centers. The assignment of virtual machines to physical machines affects energy consumption. VMP is a process of mapping VMs onto a set of PMs in a data center to minimize total power consumption and maximize resource utilization. The VMP is an NP-hard problem due to its constraints and huge combinations. In this paper, we formulated the problem as a single objective optimization problem in which the objective is to minimize the energy consumption in cloud data centers. The main contribution of this paper is hybrid and adaptive harmony search algorithm for optimal placements of VMs to PMs. HSA with adaptive PAR settings, simulated annealing and local search strategy aims at minimizing energy consumption in cloud data centers with satisfying given constraints. Experiments are conducted to validate the performance of these variations. Results show that these hybrid HSA variations produce better results than basic HSA and adaptive HSA. Hybrid HS with simulated annealing, and local search strategy gives better results than other variants for 80 percent datasets.

Three simple metaphor-less optimization algorithms are developed in this paper for solving the unconstrained and constrained optimization problems. These algorithms are based on the best and worst solutions obtained during the optimization process and the random interactions between the candidate solutions. These algorithms require only the common control parameters like population size and number of iterations and do not require any algorithm-specific control parameters. The performance of the proposed algorithms is investigated by implementing these on 23 benchmark functions comprising 7 unimodal, 6 multimodal and 10 fixed-dimension multimodal functions. Additional computational experiments are conducted on 25 unconstrained and 2 constrained optimization problems. The proposed simple algorithms have shown good performance and are quite competitive. The research community may take advantage of these algorithms by adapting the same for solving different unconstrained and constrained optimization problems.

The number of types of wire welding that circulate on the market and the development of welding technology, especially related to current welding, create a lack of information related to the quality of welding results for several types of materials. This can cause the strength of the welding connection to not be maximized. Therefore, this study aims to optimize the use of three types of wire welding and three current welding on the strength of the welding connection in two types of material testing using the response surface methodology. Box-Behnken, coupled with the RSM and the desirability function, was used to optimize the strength of the welding connection of the wire types (RD-46, LB-52, and RB-26), and current welding (100, 130, and 160 A) against two types of material testing (IWF-150 and ASTM-A517-G70). The strength of the welding connection observed in response included the tensile strength, Charpy impact-absorbed energy, hardness values in the welding metal and the hardness values in the main metal. Optimization of the strength of the welding connection in this study recommends the application of wire types RB-26, current welding of 100 A, and ASTM-A517-G70 material testing with the highest desirability value of 71.6%. Optimization of tensile strength, Charpy impact-absorbed energy, hardness values in welding metal, and hardness values in main metal by applying this parameter are 575.64 MPa, 110.69 J, 216.75 (HV10) and 126.6 (HV10), respectively. The results proved that an appropriate welding connection strength could be achieved using wire welding types and current welding in material testing.