scholarly journals Interregional Price Flexibilities: An Application to the Fed Beef Industry

1975 ◽  
Vol 7 (2) ◽  
pp. 129-133
Author(s):  
Jamal Kalantar ◽  
Russell L. Gum ◽  
Elmer L. Menzie
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
The United States ◽  
Economic Systems ◽  
Mathematical Programming Model ◽  
Beef Industry ◽  
Economic Relationships ◽  
Regional Production ◽  
Optimum Solution ◽  
The Impact

Within spatially complex economic systems, it is given that change in a commodity's production in one region engaged in interregional competition will influence the price of that commodity in all trading regions. Mathematical programming models provide useful tools to predict such price alterations for specified production changes. Unfortunately, only running and analyzing many alternative formulations of such a model can generate an understanding of the relationships among regions involved in interregional competition. Specifically, this paper addresses itself to formalizing this process and providing quantitative measures summarizing the impact of regional changes in production upon prices in all regions. This paper is concerned with quantitatively estimating the influence of a change in fed beef production for given regions upon prices of fed beef for all regions of the United States. From estimates of these relationships, economic measures of isolation of regions and the impact of changes in import levels upon regional prices will be developed. Thus, unlike much previous research in the area of interregional competition in the beef industry, focused upon finding an “optimum” solution to a mathematical programming model, this research examines the basic economic relationships among regional production and regional prices implied by an interregional competition model.

114 What Is the Impact of Dairy Influence Cattle on the Traditional Beef Industry Structure?

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 38-39
Author(s):  
Bradley J Johnson ◽  
Luke Fuerniss
Keyword(s):  
Dairy Cows ◽  
Dairy Herd ◽  
The United States ◽  
Reproductive Technologies ◽  
Industry Structure ◽  
Data Availability ◽  
Beef Production ◽  
Feed Conversion ◽  
Beef Industry ◽  
The Impact

Abstract The U.S. cow inventory includes approximately 31 million beef cows and 9 million dairy cows, so flow of cattle from dairies into beef production influences the traditional beef industry structure. Dairy-influenced cattle have historically entered the beef supply chain as cull cows and calf-fed Holstein steers. Culled dairy cows account for approximately half of the cows harvested in the United States annually. Fed steers and heifers of dairy influence are estimated to account for 15% of annual steer and heifer slaughter. Advancements in data availability, genomics, and reproductive technologies have enabled more precise selection of dairy replacement heifers and more pregnancies to be allocated to a terminal sire. Recently, the use of beef semen to breed dairy cows that are not desirable for producing replacement heifers has become more widespread. Beef-on-dairy calves are often moved to calf ranches shortly after birth where they are weaned and grown before transitioning to traditional grow yards or feedlots. In comparison to traditional range beef production, calves of dairy origin are weaned at a younger age, have more restricted mobility early in life, and are fed a delivered ration for a greater number of days. While carcasses of dairy-originated fed cattle excel in subcutaneous leanness and marbling, calves originating from dairies typically experience greater morbidity, poorer feed conversion, and poorer dressed yields compared to native fed cattle. Future opportunities to optimize beef production from the dairy herd include refining sire selection to consistently produce high quality calves, reducing variation in calfhood management, and identifying optimal nutrition and growth technology programs for calves from dairies.

scholarly journals A Mathematical Programming Model to Determine Objective Weights for the Interval Extension of TOPSIS

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hai Shen ◽  
Lingyu Hu ◽  
Kin Keung Lai
Keyword(s):  
Mathematical Programming ◽  
Input Data ◽  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Mathematical Programming Model ◽  
Topsis Method ◽  
Data Set ◽  
Interval Extension ◽  
Interval Valued

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.

CREDIBILITY-BASED FUZZY MATHEMATICAL PROGRAMMING MODEL FOR PORTFOLIO SELECTION UNDER UNCERTAINTY

2014 ◽  
Vol 13 (01) ◽  
pp. 101-135 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT ◽  
PANKAJ GUPTA
Keyword(s):  
Mathematical Programming ◽  
Portfolio Selection ◽  
Programming Model ◽  
Fuzzy Optimization ◽  
Chance Constrained Programming ◽  
Fuzzy Mathematical Programming ◽  
Mathematical Programming Model ◽  
Two Phase ◽  
Solution Approach ◽  
Practical Applications

In this paper, we develop a hybrid bi-objective credibility-based fuzzy mathematical programming model for portfolio selection under fuzzy environment. To deal with imprecise parameters, we use a hybrid credibility-based approach that combines the expected value and chance constrained programming techniques. The model simultaneously maximizes the portfolio return and minimizes the portfolio risk. We also consider an additional important criterion, namely, portfolio liquidity as a constraint in the model to make it better suited for practical applications. The proposed fuzzy optimization model is solved using a two-phase approach. An empirical study is included to demonstrate applicability of the proposed model and the solution approach in real-world applications of portfolio selection.

scholarly journals Mathematical programming models for agri-environmental policy analysis: A case study from the White Carpathians

2012 ◽  
Vol 52 (No. 2) ◽  
pp. 51-66 ◽  
Author(s):  
P. Havlík ◽  
F. Jacquet ◽  
Boisson J-M ◽  
S. Hejduk ◽  
P. Veselý
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Mathematical Programming Model ◽  
The Czech Republic ◽  
Environmental Goods ◽  
Environmental Good ◽  
Environmental Policy Analysis ◽  
Grassland Biodiversity ◽  
White Carpathians

BEGRAB_PRO.1 – a mathematical programming model for BEef and GRAssland Biodiversity PRoduction Optimisation – elaborated for analysis of organic suckler cow farms in the Protected Landscape Area White Carpathians, the Czech Republic, is presented and applied to the analysis of jointness between several environmental goods. In this way, the paper complements recent studies on jointness between commodities and non-commodities. If these goods are joint in production, agri-environmental payments must be carefully designed because they do not influence only production of the environmental good they are intended for but also the production of other environmental goods. If jointness is negative, any increase in the payment for an environmental good leads to a decrease in production of other environmental goods.

A mathematical programming model of a crop-livestock farm system

1986 ◽  
Vol 20 (4) ◽  
pp. 243-268 ◽  
Author(s):  
David A. Morrison ◽  
Ross S. Kingwell ◽  
David J. Pannell ◽  
Michael A. Ewing
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Mathematical Programming Model ◽  
Livestock Farm ◽  
Farm System
Sign in / Sign up

Export Citation Format

Share Document