Category Archives: Agricultural OR Papers

Review and position papers on the application of Operational Research to Agriculture. #ThisisOR

Application of operations research in agriculture decision making – Springer

Z. Zhang and C. Wang, Cluster analysis and optimization model of the structural distribution of aquatic industry in Huantai county, J. Qufu Teacher’s University 1(1986).

 

Z. Zhang, Present situations and prospects on the structure of agriculture and animal husbandry optimized by system engineering, J. Qufu Teacher’s University 4(1986).

 

A survey is given of applications of operations research in the area of agriculture in China, which includes farming, forestry, stock-raising, fishery, etc.

 

 

Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison

Operations research (OR) has helped people to understand and manage agricultural and forestry resources during the last 40 years. We analyzed its use to assess the past performance of OR models in this field and to highlight current problems and future directions of research and applications. Thus, in the agriculture part, we concentrate on planning problems at the farm and regional-sector level, environmental implications, risk and uncertainty issues, multiple criteria, and the formulation of livestock rations and feeding stuffs. In the forestry part, we concentrate on planning problems at the strategic, tactical, and operational levels, implementation issues, environmental implications, as well as the treatment of uncertainty and multiple objectives. Finally we made a comparison between the two areas in terms of problem types, problem-solving approaches, and reported applications.

 

A perspective on operational research prospects for agriculture : Journal of the Operational Research Society : Palgrave Macmillan

A perspective on operational research prospects for agriculture

This paper discusses the future of operational research (OR) for the agricultural industries in a broad sense, including horticulture and viticulture during a period of increased pressure on natural resources. The authors use their experience in the field along with published literature, to draw insights into new opportunities for OR, and how the OR community might adapt to realise these opportunities best. Trends in demand for food security and biofuels, the quest for sustainability, information technology (IT), and commercial power create new opportunities to support strategic investment and operations management within both primary production and the related supply chains. To realise such potential, the agricultural OR community needs to improve management of stakeholder relations, interdisciplinary synthesis, and the successful application of OR.

 

 

The Impact of Operational Research on Agriculture

The Impact of Operational Research on Agriculture
E. D. Sargent
The Journal of the Operational Research Society
Vol. 31, No. 6 (Jun., 1980), pp. 477-483
DOI: 10.2307/2580821
Stable URL: http://www.jstor.org/stable/2580821
Page Count: 7
Journal of the Operational Research Society
Journal of the Operational Research Society

Abstract

The paper shows that agriculture is one of the United Kingdom’s largest industries. It would therefore be expected that O.R. could have made a significant contribution to decision making. But achievements in practice have been disappointingly small. The industry comprises of a large number of small individual businesses which do not permit specialisation in management functions. Consequently, technical advice and much R and D is provided from public funds. O.R. applications for agriculture have mainly been developed by Universities, Colleges, State Advisory Services and QUANGOS. The paper discusses some techniques used in agriculture-linear programming, dynamic programming and simulation-and outlines some problems encountered with these. Other techniques have had limited uptake and application. Reasons for the disappointing impact of O.R. are discussed as a set of problems-those specific to farmers and their systems; those specific to computer use; problems in recruiting and training O.R. specialists and problems in communication.

 

Curated from The Impact of Operational Research on Agriculture

 

50 Years of Applying OR to Agriculture in Britain

Audsley, E., & Sandars, D. L. (2008). A review of the practice and achievements from 50 years of applying OR to agricultural systems in Britain. 116–132. Scopus.

I helped my boss Eric Audsley produce this paper (link) for the OR Society 50 conference in York 2008.  Luis Pla and I also wrote a related paper on the future prospects that made it to press at the second attempt with help from Andrew Higgins.

Audsley, E., & Sandars, D. L. (2008). A review of the practice and achievements from 50 years of applying OR to agricultural systems in Britain. 116–132. Scopus. Cite

An engineering approach for sustainable systems

This paper summed up much of the thinking and research that I had been involved with for around a decade as a research scientist at the former Silsoe Research Institute at Bedfordshire. (Wrest Park is a fabulous Stately home and was a gorgeous setting for UKs public sector agricultural engineering institute)

In many ways I remain an heir to that legacy with the remaining team members at Cranfield University. My work lies under Systems Modelling for Decisions -mostly under 1 and 2, but dipping into the rest

Key headings from the paper

Systems Modelling for Decisions:

  1. Systems modelling for environmental
  2. Whole farm decisions and land use planning -the implications of farmers’ management decisions for environmental impacts
  3. Decision support for complex uncertain systems – stochastic dynamic programming and weed control strategies
  4. Linking process and systems models to support on-farm decision making – an example for fungicide does optimization

Control Engineering approaches to biological systems:

  1. Incorporating models in the control loop
  2. Control of multiple outputs -target growth but with limited emissions
  3. Advanced sensing techniques – a route to more complex control opportunities
    1. machine vision
    2. biological sensors
  4. Real-time machine control

Day, W., Audsley, E., & Frost, A. R. (2008). An engineering approach to modelling, decision support and control for sustainable systems. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 363(1491), 527–541. https://doi.org/10.1098/rstb.2007.2168 Cite