scholarly journals Minimum Cost Multiobjective Programming Model for Target Efficiency in Sample Selection

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yousaf Shad Muhammad ◽  
Saima Khan ◽  
Ijaz Hussain ◽  
Alaa Mohamd Shoukry ◽  
Sadaf Shamsuddin ◽  
...  
Keyword(s):  
Multiobjective Programming ◽  
Programming Model ◽  
Sample Selection ◽  
Minimum Cost ◽  
Fixed Cost ◽  
Optimal Sample ◽  
Proposed Model ◽  
Compromise Allocation ◽  
Goal Programming Model ◽  
The Cost

In this study, we developed a model which elaborates relationship among efficiency of an estimator and survey cost. This model is based on a multiobjective optimization programming structure. Survey cost and efficiency of related estimator(s) lie in different directions, i.e., if one increases, the other decreases. The model presented in this study computes cost for a desired level of efficiency on various characteristics (goals). The calibrated model minimizes the cost for the compromise optimal sample selection from different strata when characteristic j is subject to achieve at least 1−αj level of efficiency of its estimator. In the first step, the proposed model minimizes the variance for a fixed cost, and it then finds the rise in cost for an αj percent rise in efficiency of any characteristic j. The resultant model is a multiobjective compromise allocation goal programming model.

scholarly journals A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianxun Cui ◽  
Shi An ◽  
Meng Zhao
Keyword(s):  
Flow Model ◽  
Time Window ◽  
Programming Model ◽  
Real Life ◽  
Minimum Cost ◽  
Emergency Evacuation ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Minimum Cost Flow ◽  
Cost Flow

During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR) function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented.

scholarly journals OPTIMALISASI PENDISTRIBUSIAN BARANG DI PT.SINAR NIAGA SEJAHTERA PALU MENGGUNAKAN METODE GOAL PROGRAMMING

2018 ◽  
Vol 15 (1) ◽  
pp. 77-85 ◽  
Author(s):  
B Hidaen ◽  
A I Jaya ◽  
Resnawati Resnawati
Keyword(s):  
Goal Programming ◽  
Programming Model ◽  
Volume Distribution ◽  
Research Results ◽  
Distribution Costs ◽  
Goal Programming Model ◽  
The Cost ◽  
Distribution Cost

PT.Sinar Niaga Sejahtera isone ofdistributorin Palu who distribute products to a variety of shops. Goal Programming is a method that can solve the problem with more than one purposes. The purposes of this study are  to maximize the number of the car and minimize the distribution  cost of  PT.Sinar Niaga Sejahtera. Goal Programming model formulationin this research consistsof 6 priorities and 6 function constraints. The sixth priorities are,warehous capacity, the number of cars used to the distribution of goods to store Sinar Kasih II,store Cahaya Indah, store Bintang  Rezeki, store Hi. Abdullah, and a minimum distribution costs. Constraint functions consist of a number of cars and the cost of distribution. The research results showed that the supply of goods by the warehouse capacity that can fulfiil the necessary distribution of goods during the month amounted to 136.93 or 8.628 box Optimal volume distribution of goods in each store are sequentially Sinar Kasih II which is 2 units with a capacity of 4  or 252 box, Cahaya Indah 3 units with a capacity of 7  or 441 box, Hi. Abdullah 2 units with a capacity of 12 or 756 box and Star 2 cars Rezeki capacity of 4 . This model can save the distribution costs of Rp. 7.127.147 from the previous distribution costs of Rp. 35.000.000.

scholarly journals Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Farnaz Javadi Gargari ◽  
Mahjoube Sayad ◽  
Seyed Ali Posht Mashhadi ◽  
Abdolhossein Sadrnia ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Supply Chain ◽  
Optimization Model ◽  
Optimization Problem ◽  
Programming Model ◽  
Transportation Cost ◽  
Real Data ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Hub Location ◽  
Goal Programming Model

Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

scholarly journals Lexicographic Goal Programming Model for Bank’s Performance Management

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ali AlArjani ◽  
Teg Alam
Keyword(s):  
Saudi Arabia ◽  
Performance Management ◽  
Goal Programming ◽  
Financial Management ◽  
Programming Model ◽  
Financial Statements ◽  
Operating Income ◽  
Proposed Model ◽  
Goal Programming Model ◽  
Lexicographic Goal Programming

Any bank’s financial management is essential to preparing the assets and liabilities for multiple goals. In this paper, we develop an optimal bank model for the financial management department in the Kingdom of Saudi Arabia. The lexicographic goal programming model was used to formulate the banks’ performance management. In this study, the six goals of one of the leading banks in Saudi Arabia, namely, maximize asset, minimize liability, maximize equity, maximize operating income, maximize net income, and maximizing total goal achievements in the financial statement, were studied. To illustrate the model, we have focused on Al Rajhi Bank’s financial statements as a case study. The data was obtained from the banks’ financial statements. The outcomes of the study exhibited that all goals were accomplished. This proposed model is dynamic because it will help examine the banks’ financial strengths located in the kingdom. As a result, the proposed model can guide banking firms in making decisions and developing strategies to deal with numerous monetary circumstances.

scholarly journals An Analysis of the Effects of Feed Ingredient Price Risk on the Selection of Minimum Cost Backgrounding Feed Rations

2001 ◽  
Vol 33 (2) ◽  
pp. 353-365 ◽  
Author(s):  
Brian K. Coffey
Keyword(s):  
Programming Model ◽  
Minimum Cost ◽  
Price Risk ◽  
Net Income ◽  
Income Risk ◽  
Decision Tools ◽  
Price Series ◽  
Feed Costs ◽  
The Cost ◽  
Selection Of

AbstractThe traditional minimum cost feed ration linear programming model is expanded to permit risk management responses to price variability associated with feeding a particular ration across time. The cost minimizing objective function also considers feed costs in a mean-variance (E-V) framework. The model is specified using NRC nutrient requirements and an historic Feedstuffs price series. A decision-maker can choose his/her optimal ration by making tradeoffs between price risk and net income. The results should provide a basis for decision tools that allow livestock producers to manage the net income risk involved in the selection of a feed ration.

Improved Model to Determine the Tool Life and the Cutting Speed for Minimum Cost at Drilling the Steel 10TiMoNiCr175

2013 ◽  
Vol 837 ◽  
pp. 234-238
Author(s):  
Aurelian Vlase ◽  
Ovidiu Blăjină ◽  
Vlad Darie
Keyword(s):  
Tool Life ◽  
Programming Model ◽  
Cutting Speed ◽  
Minimum Cost ◽  
Machining Process ◽  
Manufacturing Activity ◽  
Nonlinear Programming Model ◽  
Improved Model ◽  
The Cost ◽  
Accuracy Of Prediction

In the specialized literature the cost of the machining process has been analyzed using a number of approaches and varying degrees of simplification to determine the optimum tool life and the tool speed. The accuracy of prediction is dependent on the degree of sophistication of the model. The purpose of this paper is the optimization of the cutting tool life and the cutting speed at the drilling of the stainless steels in terms of the minimum machining cost. A more comprehensive nonlinear programming model to minimize the total cost at the drilling of a stainless steel is developed in this paper. The optimum tool life and the associated tool speed are obtained by solving this model. The results can be taken into consideration in the educational studies and in the theoretical technical research. They can be implemented in the manufacturing activity.

scholarly journals Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Xuejie Bai
Keyword(s):  
Programming Model ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Optimization Method ◽  
Allocation Problem ◽  
Two Stage ◽  
Whole Process ◽  
Proposed Model ◽  
Goal Programming Model ◽  
Computational Difficulty

This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.

scholarly journals Binary goal programming model for optimizing tire selection using branch and bound algorithm

2021 ◽  
Vol 12 ◽  
pp. 8
Author(s):  
Shady Aly
Keyword(s):  
Decision Making ◽  
Branch And Bound ◽  
Goal Programming ◽  
Programming Model ◽  
Operating Conditions ◽  
Branch And Bound Algorithm ◽  
Adoption Decision ◽  
Proposed Model ◽  
Goal Programming Model ◽  
Design Selection

The problem of assessment and adoption of automotive tyre design specifications has not been addressed sufficiently in literature. This is in spite of its significance as a crucial component relevant to design and safety of the automobile. In this paper, a multi-objective optimization model of the tyre design trademark adoption decision is proposed. Multi-attribute or multi-criterion decision making techniques are heuristics providing good solution, but do not guarantee optimum solution. Up to date, there is no optimal yielding method for selection of vehicle tyre manufacturer or trademark based on prespecified design targets. The proposed model is formulated as a binary goal programming model for optimizing tyre trademark design selection decision by adopting an optimal tyre design trademark that best achieve design targets. The model is solved by the branch and bound algorithm. One advantage of the proposed model is flexibility to incorporate multiple design targets, tolerance limits and different constraints. The proposed model can support efficient and effective decision making concerning the adoption of tyre trademark design for new automobile or to re-adopt new design for new road vehicle operating conditions.

scholarly journals Economic growth, nutrition and living standards in 19th century Lima: new estimates of welfare ratios using a linear programming model

2021 ◽  
Vol 28 (3) ◽  
pp. 1-24
Author(s):  
Luis Felipe Zegarra
Keyword(s):  
Linear Programming ◽  
19Th Century ◽  
Programming Model ◽  
Basic Needs ◽  
Minimum Cost ◽  
Living Standards ◽  
Linear Programming Model ◽  
Skilled Workers ◽  
Food Basket ◽  
The Cost

This study relies on a linear programming model to estimate welfare ratios in 19th century Lima. By using a linear programming model, the food basket guarantees the intake of basic nutrients at the minimum cost. The subsistence cost includes the cost of food and other basic needs. The estimates show that low-skilled workers in Lima were able to cover their basic needs in 1800-1875. The results also show that living standards of low-skilled workers declined during the Guano Era. Living standards in Lima, however, compared favorably to several cities in Europe.

scholarly journals An Optimization to Schedule Train Operations with Phase-Regular Framework for Intercity Rail Lines

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Huimin Niu ◽  
Minghui Zhang
Keyword(s):  
Programming Model ◽  
Hybrid Genetic Algorithm ◽  
Minimum Cost ◽  
Proposed Model ◽  
Rail Line ◽  
Service Oriented ◽  
Scheduling Method ◽  
Train Length ◽  
Crossover And Mutation ◽  
Dependent Demand

The most important operating problem for intercity rail lines, which are characterized with the train operations at rapid speed and high frequency, is to design a service-oriented schedule with the minimum cost. This paper proposes a phase-regular scheduling method which divides a day equally into several time blocks and applies a regular train-departing interval and the same train length for each period under the period-dependent demand conditions. A nonlinear mixed zero-one programming model, which could accurately calculate the passenger waiting time and the in-train crowded cost, is developed in this study. A hybrid genetic algorithm associated with the layered crossover and mutation operation is carefully designed to solve the proposed model. Finally, the effectiveness of the proposed model and algorithm is illustrated through the application to Hefei-Wuhan intercity rail line in China.

Sign in / Sign up

Export Citation Format

Share Document