PENILAIAN LALUAN PERKHIDMATAN BAS; ANTARA BILANGAN PENUMPANG MAKSIMUM ATAU KEPADATAN PENUMPANG PER LALUAN

2016 ◽  
Vol 78 (2) ◽  
Author(s):  
Ruslawati Abdul Wahab ◽  
Muhamad Nazri Borhan ◽  
Riza Atiq Abdullah O.K. Rahmat
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Travel Time ◽  
Main Issue ◽  
Operational Cost ◽  
City Bus ◽  
Shortest Distance ◽  
Bus Services ◽  
The Mathematical Model ◽  
Better Than

The main issue in Putrajaya’s bus services is related to time and cost. Optimal travel time require optimal routes and shortest distance. Minimizing travel time means minimizing operational cost. This paper reviews and evaluates the density of passengers and maximum number of passengers as parameters to obtain an optimum route. The mathematical model was utilized to analyze the passenger density with the improvements of the constraint to the number of passengers. The study based on data from intra-city bus services during off-peak hours. The main focus of this optimization is to compare the passenger density and the number of passengers as the parameters in decision making for bus routes. The result shows that the passenger density is better than the number passengers to assess bus routes.

Balancing of parallel U-shaped assembly lines with a heuristic algorithm based on bidirectional priority values

2021 ◽  
pp. 1063293X2110655
Author(s):  
Yuling Jiao ◽  
Xue Deng ◽  
Mingjuan Li ◽  
Xiaocui Xing ◽  
Binjie Xu
Keyword(s):  
Mathematical Model ◽  
Heuristic Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Assembly Lines ◽  
Line System ◽  
Assembly Line Balancing Problem ◽  
The Mathematical Model ◽  
Better Than

Aiming at improving assembly line efficiency and flexibility, a balancing method of parallel U-shaped assembly line system is proposed. Based on the improved product priority diagram, the bidirectional priority value formula is obtained. Then, assembly lines are partitioned into z-q partitions and workstations are defined. After that, the mathematical model of the parallel U-shaped assembly line balancing problem is established. A heuristic algorithm based on bidirectional priority values is used to solve explanatory examples and test examples. It can be seen from the results and the effect indicators of the assembly line balancing problem that the heuristic algorithm is suitable for large balancing problems. The proposed method has higher calculation accuracy and shorter calculation time. The balancing effect of the parallel U-shaped assembly line is better than that of single U-shaped assembly line, which verifies the superiority of the parallel U-type assembly line and effectiveness of the proposed method. It provides a theoretical and practical reference for parallel U-type assembly line balancing problem.

Cost Element Modelling, Prediction and Optimization in a Dual-Completion Well During a Coiled Tubing Unloading Operation

2021 ◽  
Author(s):  
Merit P. Ekeregbe
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Cost Estimation ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Correct Prediction ◽  
Reservoir Pressure ◽  
Gas Industry ◽  
Coiled Tubing ◽  
The Mathematical Model

Abstract In an era where cost is a significant component of decision making, every possibility of reducing operational cost in the Oil and Gas industry is a welcome development. The volatile nature of the Oil market creates uncertainty in the industry. One way to manage this uncertainty is by the ability to predict and optimize our operations to reduce all of our cost elements. When cost is planned and predicted as accurately as possible, the operation optimizations can be managed efficiently. Practically, all new drills require CT unloading of the completion or kill fluids to allow the natural flow of the wells. Hitherto, there is no mathematical model that combines information from one of the wells in an unloading dual completion project that can be used to aid decision-making in the other well for the same unloading project and thereby result in an effective cost-saving. Deploying the mathematical model of cost element prediction and optimization can minimize operational unloading costs. The two strings of the dual completion flow from different reservoirs. Still, the link between the two drainages post completion is the kill fluid density, and can aid in cost estimation for optimum benefit. The lesson learned or data acquired from the lifting of the slave reservoir string can be optimized to effectively and efficiently lift the master reservoir string. The decision of first unloading the slave reservoir string is critical for correct prediction and optimization of the ultimate cost. The mathematical model was able to predict the consumable cost elements such as the gallon of nitrogen and time that may be spent on the long string from the correlative analysis of the short string. The more energy is required for unloading the short string and it is the more critical well than the long string because it is the slave string since no consideration as such is given to it when beneficiating the kill fluid to target the long string reservoir pressure with a certain safety overbalance. The rule for the mud weight or the weight of the kill fluid is the highest depth with highest reservoir pressure which is the sand on the long string. With the data from the short string and upper sand reservoir, the lift depth and unloading operation can be optimized to save cost. The short string will incur the higher cost and as such should be lifted last and the optimization can be done with the factor of the LS.

Cooperative Target Allocation for UCAV Team Air-to-Ground Attack Based on Decision Graph Bayesian Optimization Algorithm

2012 ◽  
Vol 457-458 ◽  
pp. 655-662
Author(s):  
Lu Cao ◽  
An Zhang ◽  
Feng Juan Guo
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Bayesian Optimization ◽  
Bayesian Optimization Algorithm ◽  
Decision Graph ◽  
Target Allocation ◽  
Cooperative Decision Making ◽  
The Mathematical Model

In order to control and optimize cooperative air-to-ground attack decision-making of the unmanned combat aerial vehicle (UCAV) team, the principle of income maximum and loss minimum of UCAV team is built firstly. Accordingly, the mathematical model of cooperative target allocation is built based on the decision variables and constraints. Then Bayesian optimization algorithm (BOA) is introduced which is one kind of the evolution algorithm. For improving the ability of the BOA, decision graph is introduced to enhance the represent and learn of Bayesian network and compress the parameter saving. Finally decision graph Bayesian optimization algorithm (DBOA) is utilized to optimize and analyze the model. The simulation results verify that the mathematical model of cooperative target allocation can reflect the importance of cooperative decision-making, the DBOA can converge quickly to the global optimal solution and can effectively solve the cooperative target allocation problem of UCAV team air-to-ground attack.

An accurate and efficient control over the present numerical model of depth of sputtering in focused ion beam milling

2009 ◽  
Vol 223 (1) ◽  
pp. 9-18 ◽  
Author(s):  
S N Bhavsar ◽  
S Aravindan ◽  
P Venkateswara Rao
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Substrate Material ◽  
Milling Process ◽  
Intensity Function ◽  
Two Parameters ◽  
The Mathematical Model ◽  
Better Than

In many applications, such as fabrication of microtools, microsurgical instruments, microgears, and so on, material must be removed precisely with a focused ion beam (FIB) milling process to generate a specified geometry on substrate material. A mathematical model is available to calculate depth of sputtering at each point on substrate material in order to generate a specified geometry, but the results of the existing model deviates from experimental data. In the current paper, normalized pixel spacing and ratio of redeposition to beam velocity are the two parameters that have been considered in calculation of depth of sputtering during the FIB milling process. A proposed mathematical model incorporating the effect of redeposition has been simulated for parabolic and rectangular trench profiles, and it has been proven to be better than the existing model through comparison with experimental data of parabolic and rectangular geometry on silicon material. In addition, efforts have been made to reduce the amount of numerical calculation in the simulation process by utilizing a Gaussian mask in the existing model instead of the usual Gaussian intensity function. The Gaussian mask prevents the need for repeated calculation of Gaussian intensity function in the mathematical model of depth of sputtering, and in turn reduces the time of computation.

scholarly journals New Method of Path Optimization for Medical Logistics Robots

2021 ◽  
Vol 33 (4) ◽  
pp. 944-954
Author(s):  
Hui Jin ◽  
Qingsong He ◽  
Miao He ◽  
Fangchao Hu ◽  
Shiqing Lu ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Optimization Procedure ◽  
Planning Problem ◽  
Time Cost ◽  
Problem Model ◽  
Acceleration And Deceleration ◽  
The Mathematical Model ◽  
Path Planning Problem ◽  
Better Than

The path planning problem of logistics robots is mainly subjected to the time cost of the operation of the mathematical model. To save the time of refilling process in the fast medicine dispensing system (FMDS), the optimization procedure is divided into two steps in this study. First, a new mathematical model called the multiple steps traveling salesman problem model (MTSPM) is proposed to optimize the replenishment quantity of each picking and establish picking sets. Second, an improved ant colony optimization (IACO) algorithm is employed, considering the effects of velocity, acceleration, and deceleration in the refilling route during the development of the new model. Simulation results and operational results demonstrated that MTSPM-IACO was better than both the order picking model (OPM) and MTSPM-ACO in terms of saving refilling time. Compared to the OPM, the optimization of the refilling time of MTSPM-IACO was more than 1.73% in simulation and 15.26% in operation. Compared to MTSPM-ACO, the optimization of the refilling time of MTSPM-IACO was more than 0.13% in simulation and 1.67% in operation.

The Composite Method of Torque Ripple Restraining in Brushless DC Motor

2013 ◽  
Vol 385-386 ◽  
pp. 1171-1174
Author(s):  
Hai Peng Pan ◽  
Jun Jie Gu ◽  
Min Ming Gu
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Torque Ripple ◽  
Dc Motor ◽  
Physical Structure ◽  
Brushless Dc Motor ◽  
Current Compensation ◽  
Brushless Dc ◽  
The Mathematical Model ◽  
Better Than

Brushless DC motor generates parasitic torque ripple owing to its physical structure. The consequences deteriorate the performance of the drive in demanding applications. The mathematical model is analyzed. A fast toque control system employed which combines the current compensation and PWM_ON_PWM modulation. The effectiveness of the adaptive torque ripple compensation is demonstrated by experiments which is better than its using PWM_ON_PWM alone.

Improving decision making in product flow-based tiling automation for custom mosaic design

2017 ◽  
Vol 37 (4) ◽  
pp. 391-399 ◽  
Author(s):  
Panitcha Peganant ◽  
Pisut Koomsap
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Simple Cycle ◽  
Automated Assembly ◽  
Content Type ◽  
Labview Software ◽  
Product Flow ◽  
Shortest Distance ◽  
Better Than

Purpose The purpose of this paper is to present a new tile dispensing decision-making to improve a row formation of a product flow-based tiling automation that has been being developed to support tile placement for custom mosaic design. Design/methodology/approach A new tile dispensing decision-making combines maximum tile loading and simple cycle strategies to minimize time for forming rows of tiles. The maximum tile loading strategy is for minimizing the number of loading rounds, while the simple cycle strategy is for minimizing the movement during the row formation. Findings This proposed decision-making has been developed; implemented in LabVIEW software; linked with other LabVIEW-based programs to control the system; and tested. The results showed the tile dispensing with the proposed decision-making performed better than the previous one. Research limitations/implications The tiling automation is being developed and is currently on a prototyping stage. Originality/value Tile dispensing is critical for this row by row automated assembly, but the existing shortest distance strategy does not guarantee the best performance for a row formation. Therefore, the combination of the maximum tile loading and simple cycle strategies has been developed to improve the performance of the product flow-based tiling automation to better support assembly of custom mosaic design that requires individual tesserae to be assembled to particular positions to illustrate an image properly.

scholarly journals The Art and Science of Modeling Decision-Making Under Severe Uncertainty

2007 ◽  
Vol 1 (2) ◽  
pp. 111-136 ◽  
Author(s):  
Moshe Sniedovich
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Decision Making ◽  
Case Analysis ◽  
Worst Case Analysis ◽  
Art And Science ◽  
Worst Case ◽  
Severe Uncertainty ◽  
The Mathematical Model

For obvious reasons, models for decision-making under severe uncertainty are austere. Simply put, there is precious little to work with under these conditions. This fact highlights the great importance of utilizing in such cases the ingredients of the mathematical model to the fullest extent, which in turn brings under the spotlight the art of mathematical modeling. In this discussion we examine some of the subtle considerations that are called for in the mathematical modeling of decision-making under severe uncertainty in general, and worst-case analysis in particular. As a case study we discuss the lessons learnt on this front from the Info-Gap experience.

scholarly journals APPLICATION OF THE SIR MODEL TO COVID-19: social distance and (no-)evolution of the pandemic in state of the Tocantins

2020 ◽  
Vol 6 (3) ◽  
pp. a16en
Author(s):  
Élis Gardel da Costa Mesquita ◽  
Janeisi de Lima Meira ◽  
José de Ribamar Leonel Dias Neto
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Social Distance ◽  
Sir Model ◽  
System Of Differential Equations ◽  
Public Power ◽  
The Social ◽  
Isolation Index ◽  
The Mathematical Model ◽  
Reproduction Factor

This article is a study about the behavior and spread of the Covid-19 pandemic, in the state of Tocantins, based on data reported from March 18 to June 10. A modification of the mathematical model SIR was used, in which some auxiliary compartments were added. We analyzed epidemic aspects such as the speed of the contagion curve and its impacts on the health system. As the data are made available daily, a discretization of the system of differential equations that make up the model was performed, and based on the availability of known data, we investigated the correlation between the social isolation index and the basic reproduction factor.  Through a very simple interpolation, approximate contagion rates were obtained, enabling us to evaluate the behavior of the evolution of contagion curves and those that depend on them, which allows us to anticipate scenarios based on the trend lines of the data generated, thus helping decision making public power.

Improvement of the Algorithm of Algebraic Constructive Logic Model

2015 ◽  
Vol 22 (2) ◽  
pp. 11-19 ◽  
Author(s):  
Хромушин ◽  
Oleg Khromushin ◽  
Хромушин ◽  
Viktor Khromushin ◽  
Китанина ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Multivariate Analysis ◽  
Final Stage ◽  
Detection Limits ◽  
Algebraic Model ◽  
Logic Model ◽  
Constructive Logic ◽  
Partial Overlap ◽  
The Mathematical Model ◽  
Better Than

For many years, algebraic constructive logic model is used for multivariate analysis in medicine and biology. The classic version of this model includes the exclusion of contradictory accounts, i.e. when the target is achieved and not achieved in the presence of the same values of the factors. In this case, the lines as appropriate to achieving target, and its failure are removed, including significant proportions. Another feature of this algorithm is the partial overlap of the intervals to determine the factors resulting in components in achieving a target and not achieving despite the exclusion of contradictory accounts. The authors explain this by the fact that the classical algorithm generates the detection limits of the factors in resulting components with some capture values that are related to the lines of not achieving the target (up to inappropriate values). To some extent this reduces the accuracy of the mathematical model. A further feature of the algorithm is the necessary to optimize mathematical model by excluding re-coating lines. This is acceptable, but not optimal. This requires additional procedures at the final stage of formation of the mathematical model. The proposed version of the algebraic model of constructive logic allows to eliminating the above drawbacks. This is achieved the measure of approximation and a way of combining the cases in the resulting components. The proposed algorithm was tested using specially designed software that allows to exclude controversial cases and to form a mathematical model. Testing showed that the proposed algorithm is better than the classic version and meets the objectives of multivariate analysis in medicine and biology.

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