A comparative study of several nature-inspired algorithms in steel deck floor system cost optimization

Steel deck floor systems can be considered as one of the main components of a structure. As technology advances, the role of optimization is used in many aspects of structural designs. Steel deck floor systems are one of many components that are usually optimized to look for its optimum cost but are still able to hold the structure. This study compares the performance of the particle swarm optimization (PSO), artificial bee colony (ABC), differential evolution (DE), and symbiotic organisms search (SOS), that categorized as nature-inspired algorithms, in the optimization of a steel deck floor system. The variables considered are the edge beams, interior beams, and the composite steel deck. The results show that the SOS gives the most optimum cost with a better average and a perfect success rate.

Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area

The spread of electric vehicles (EV) contributes substantial stress to the present overloaded utility grid which creates new chaos for the distribution network. To relieve the grid from congestion, this paper deeply focused on the control and operation of a charging station for a PV/Battery powered workplace charging facility. This control was tested by simulating the fast charging station when connected to specified EVs and under variant solar irradiance conditions, parity states and seasonal weather. The efficacy of the proposed algorithm and experimental results are validated through simulation in Simulink/Matlab. The results showed that the electric station operated smoothly and seamlessly, which confirms the feasibility of using this supervisory strategy. The optimum cost is calculated using heuristic algorithms in compliance with the meta-heuristic barebones Harris hawk algorithm. In order to long run of charging station the sizing components of the EV station is done by meta-heuristic barebones Harris hawk optimization with profit of USD 0.0083/kWh and it is also validated by swarm based memetic grasshopper optimization algorithm (GOA) and canonical particle swarm optimization (PSO).

Mathematical Modelling of Bifacial Dual SIS Solar Cell and Optimization of Tilt Angle

The major challenge of PV cell design and installation has always been to find the optimum cost per energy and area of installation of solar panels. In densely populated and high-yielding agricultural country like India land acquisition is becoming an issue. Moreover the consisting demand to deduce the cost per energy indulges the worldwide scientists to design more efficient solar cells with low production cost. In developing countries scientists and engineers are trying to find an amicable solution to meet up these problems. In this paper the mathematical modelling of a dual SIS bifacial vertically mounted solar panel has been proposed to mitigate the energy and land area crisis in countries of Indian subcontinent, south Asia and elsewhere. The SIS (Semiconductor-Insulator-Semiconductor) technology was chosen for its extremely low thermal budget and less complicated production procedure. A bifacial solar cell with SIS junction in both sides was modelled. The front surface SIS junction was considered ZnO-SiO2-Si(p-type) while the back surface junction was considered Si(p type)-Al2O3-SnO. The efficiency for front and back surface was calculated as 5.64% and 5.58% respectively. We have further considered the effect of albedo from two different surfaces (soil and concrete) and the efficiencies of front and back surface for these albedo radiations. The angle of installation was optimized for both these effects. Considering both direct and albedo the all-day efficiency was calculated as 22.47% for a sunny day tropical region.

Optimum Design of Combined Rectangular RCC Footing using GA

The paper presents an estimation of the optimum cost of an isolated and combined footing following the safety and serviceability guidelines of Indian Standard (IS) 456:2000. The optimization methods, i.e., genetic algorithm, with static penalty function approach is developed in MATLAB compliant for optimal design of isolated and combined rectangular footing. The objective function formulated is based on the total cost of footing which includes the cost of concrete, steel and formwork. The influence design variables the total cost of footing are length, width and depth of footing and area of steel(flexural) reinforcement for moment at critical sections. The footing design algorithm is developed according to the biaxial-isolated and biaxial-combined rectangular footing as per IS codes. The constraints, e.g., dimension of footing, restriction on bending, shear stresses and displacements, are considered in the footing design algorithm which acted as a subroutine to the developed optimization programs. Five numerical examples have been taken to solved and evaluate the versatility of the developed method and observe the efficacy of method.

Structural optimization of a composite launch tube of man portable air defense system

Purpose The purpose of this paper is to find the optimum configuration of the composite launch tube currently being developed in Roketsan. The winding thicknesses and winding angles of the launch tube are selected as design variables, and three different composite material alternatives are evaluated: glass/epoxy, carbon/epoxy and aramid/epoxy. Design/methodology/approach In this study, structural optimization of a composite launch tube of man portable air defense system is conducted. To achieve a cost-effective design, a cost scoring table that includes structural weight, material cost, availability and manufacturability is first introduced. Then, optimization for minimum weight is conducted, where the winding thicknesses and winding angle are taken as design variables, and the safety factor value obtained by using the Tsai–Wu damage criterion is used as constraint. A surrogate-based optimization approach is used where various options for surrogate models are evaluated. Glass/epoxy, carbon/epoxy and aramid/epoxy are considered as alternative materials for the launch tube. Finally, the selection of the most cost-effective design is performed to achieve optimum cost. Findings Carbon fiber-reinforced epoxy matrix material provides the optimum cost-effective design for the launch tube. Practical implications The findings of the paper can be used to design more cost-efficient composite launch tube currently being developed in Roketsan. Originality/value The existing studies are based on a design approach to achieve minimum weight of the launch tubes, whereas this study introduces a design approach to achieve optimum cost.

Predicting Cost Contingency Using Analytical Hierarchy Process and Multi Attribute Utility Theory

An endeavor to predict the optimum contingency value that balances between maintaining business competitiveness and achieving project objectives is definitely an essential contributor to the survival of contractors. The chief objective of this research, therefore, is to develop a mathematical prediction model of the optimum cost contingency value for building projects in Saudi Arabia. The analytical hierarchy process (AHP) technique was used to define the most significant risk factors inherent in public work projects. The multi attribute utility theory (MAUT) technique was used to measure contractors’ risk attitudes and to establish the utility functions through MATLAB. The required data to build the model for the AHP and MAUT were collected from 17 contractors mostly through intensive face-to-face interviews and email-response to a developed structured questionnaire. The integrated contingency model reflects the basic dimensions of risk and considers the various risk attitudes of contractors. The model has been implemented in prototype software using object-oriented programming. Two completed local building construction projects were used to validate and demonstrate the use of the developed model in recommending the optimum cost contingency value for building projects in Saudi Arabia. The developed model was proven reliable in estimating the contingency with an accuracy skewed 9% to the high side.

Conceptual Framework on information technology and supply chain management on operational performance in Construction companies

Project management is a very important discipline that acts to enhance operational performance. therefore, the project has a timeframe to finalize the project in proper quality and time with optimum cost. the objective of this study is to identify a conceptual framework that links the information technology used with supply chain management to improve the operational performance in construction companies, which considered essential tasks to ensure the quality of the product and services during approval and supplying stage. The problem is the absence of some advanced technologies to control and monitoring supply chain management in some of the construction industries. This study will focus on the big size, construction companies in the sultanate of Oman to get an efficient and effective result.

Overstock Improvement by Combining Forecasting, EOQ, and ROP

Optimum stock inventory level is an essential factor in inefficient production. Overstock is an obstacle to achieving optimum cost. The purpose of this paper is to provide solutions in overstock in the electronic spare parts industry by comparing the various approaches Forecasting, EOQ, ROP with DDMRP to get the best model to obtain the inventory level Optimally. The Reset is done on the material Copper wire 0, 14mm as the primary material, which is the most expensive material and widely used in production activities. The results of this study showed that the method of DDMRP could decrease the average amount of the supply of Copper wire 0, 14mm per month from 2779 kg to 1499 kg.

Crop-machinery management system for field operations and adopted planning techniques for plantation sugar cane production

Major objectives of farm mechanization are to maximize production at minimum risks and optimum cost of equipment usage by good management planning and operation of machines to carry out sequence crop production operations for the whole farming system. Hence this study was needed at Sunti Golden Sugar Company, Nigeria to determine cost of equipment use and select appropriate tractor power and machinery for the crop cultivation, crop establishment, weed control, cane harvesting and transporting to the store for post-harvest processing for future target of 4,770 ha of sugar cane farm. Based on agricultural farm size, field operational planning factors like soil, weather/environmental conditions, each implement matched with appropriate tractor size was calculated. Costs of equipment use, ownership and operational costs for implements and tractors were also calculated. A well-drawn cropping field operations calendar was very important for crop and operational sequencing was recommended and was put in-place since the operations overlaps with multi-periods. As part of the recommendation, during the planned equipment downtime, major repairs and maintenance were to be carried out before critical field operation's period to improve pre-field and in-field efficiency for effective equipment and field operational planning and management. Determined are the values of each implement field capacity within allotted time available, actual number of implement/tractor power required, fuel and oil consumption per unit time for the sugar cane cultivation, harvesting and transporting operations at the sugar cane farm. Also appropriate earth-moving and earthwork equipment for road, irrigation and drainage structural works were also selected.

Profitability variations and disparity in automobile sector: A case of leading Indian Automobile companies

The Indian automobile sector is the biggest market and emerging by displacing some advanced countries. The Indian automobile sector contributes positively and progressively to the growth and development of the Indian economy. The study is based on secondary data and considers the financial statements available on concerned websites. Ratio analysis, ANOVA (Analysis of Variance), CV (Coefficient of Variation), and rank correlation applied to analyze the data extracted from the financial statements of leading Indian automobile companies. The study reveals that there is a significant difference in the profitability of the Leading Indian automobile companies for the period 2011 to 2020. There is a moderate positive relational relationship between PBDIT(Profit Before Depreciation, Interest, and Tax) ratio and PBIT(Profit Before Interest and Tax) ratio and their variability while PBT ( Profit Before Tax) ratio and PAT ( Profit After Tax) ratio and their variability positively and highly correlated. This reveals that manufacturing expenses and depreciation do not affect profitability while profitability governs the interest and taxes of the leading Indian automobile companies. The study suggests a possible reduction in all direct and indirect costs, optimum cost of capital, or low cost of capital structure can be considered to avoid excessive burden against the profits of the negative performing leading Indian automobile sector companies.