Multiple Goal Linear Programming Research Articles

Land use allocation based on multi-goal linear programming model: a case study of Central Luzon State University

Allocating and reallocating land resources is critical to a long-term land use planning and is a key component to achieve a balanced land use system. This provides appropriate space for varied land uses while preserving the environment for future generations. It is found to be an excellent measure for development and sustainability of an area. Using multiple goal linear programming as a decision support system, this study highlighted the optimization of land use allocation at Central Luzon State University to meet the needs for sustainable development. All the seven (7) general land use classifications determined in the University: agricultural, institutional, residential, commercial, fisheries (pond/fish tanks), roads and open areas were assessed in crafting the Land Use Development and Infrastructure Plan (LUDIP) for 2021 to 2031. The findings demonstrated that the priority goals set by the CLSU constituents: (1) minimizing disaster risk, (2) maximizing land suitability, (3) maximizing research capability, maximizing social development, and maximizing economic value were achieved with the aid of Gurobi. Agricultural and commercial growth, residential, social, and infrastructure development for all constituents, research development, climate change adaptation, and cultural heritage preservation were all aided by the land use optimization in the LUDIP.

Towards sophisticated decision models: Nonadditive robust ordinal regression for preference modeling

This paper addresses a methodology for decision support under multiple and correlated decision criteria. Nonadditive robust ordinal regression (NAROR) aims to build capacities that fit the decision makers’ explicit preferences and pairwise rankings of some alternatives. The capacities provide great flexibility to model decision problems accounting for interactions among the decision criteria. The feasible set of capacities helps identifying all the necessary and possible dominance relations among all the decision alternatives. In this paper we enhance the NAROR method by identifying optimal capacities through entropy maximisation. We formulate suitable optimisation problems and provide avenues for capacity simplification based on k-interactivity. We also consider the situation of large number of sparse constraints, for which we formulate a linear program based on Renyi entropy. We deal with preferences inconsistency by using multiple goal linear programming technique. The results show that the k-interactivity is an efficient way to reduce the complexity of capacities while preserving their expressiveness and representation ability, and that optimal capacities can be found by standard mathematical programming techniques.

Multiple Goal Linear Programming-Based Decision Preference Inconsistency Recognition and Adjustment Strategies

The purpose of this paper is to enrich the decision preference information inconsistency check and adjustment method in the context of capacity-based multiple criteria decision making. We first show that almost all the preference information of a decision maker can be represented as a collection of linear constraints. By introducing the positive and negative deviations, we construct the the multiple goal linear programming (MGLP)-based inconsistency recognition model to find out the redundant and contradicting constraints. Then, based on the redundancy and contradiction degrees, we propose three types of adjustment strategies and accordingly adopt some explicit and implicit indices w.r.t. the capacity to test the implementation effect of the adjustment strategy. The empirical analyses verify that all the strategies are competent in the adjustment task, and the second strategy usually costs relatively less effort. It is shown that the MGLP-based inconsistency recognition and adjustment method needs less background knowledge and is applicable for dealing with some complicated decision preference information.

Nonadditive robust ordinal regression with nonadditivity index and multiple goal linear programming

Nonadditive robust ordinal regression (NAROR) is a widely adopted approach to analyze and reveal the dominance relationships among all decision alternatives based on nonadditive measures, called capacities. In this paper, we first investigate some advantages of the nonadditivity index as an explicit interaction index, as compared with the traditional probabilistic simultaneous interaction indices, and show that nonadditivity index can serve as an equivalent representation of a capacity. Then we enhance the NAROR method by using nonadditivity index as well as multiple-goal linear programming, where the former is used to replace the traditional interaction index to more naturally represent the decision maker's preferences, and the latter aims to replace the 0 to 1 mixed integer programming to enhance the ability to detect and adjust contradictory and redundant preference information. The updated NAROR's steps are constructed and discussed in detail and illustrated with a practical example.

Optimization of agricultural biogas supply chains using artichoke byproducts in existing plants

The development of biogas production exacerbated the competition for land availability between crops dedicated to human consumption and those intended for energy production. Residual biomasses have been often proposed for their positive outcomes in terms of reduced pressure on land use. However, literature did not assess optimization options for existing biogas plants feeding. This paper developed a bio-economic model for the optimization of agricultural biogas supply chains using artichoke byproducts in existing plants. A multiple goal linear programming approach was adopted, using two objective functions, calculating respectively net present value and land use from energy crops, associated to a regional biogas network. Three scenarios were defined using primary and secondary data on the residues of a specific artichoke variety - globe - and an Italian region - Sardinia. In the Business As Usual scenario, net present value is about 7 million € with a land use of about 2720 ha. When using artichoke residues, the economic impact increases by 28% and land use is reduced by 83% if net present value is optimized. When land use is optimized, the economic impact still grows by 25% and land use is reduced by 100%. Results from this study confirm that, under certain conditions, locally available residual biomasses can replace energy crops in existing biogas networks, coupling viability and sustainability.

Exploring sustainable farming scenarios at a regional scale: an application to dairy farms in Brittany

The objective of this study was to model land use configuration for a sustainable dairy sector in Brittany, France, using results from Life Cycle Assessment (LCA) in Multiple-Goal Linear Programming (MGLP). To generate future land-use configurations that met environmental targets, the approach required (1) defining a set of current and alternative land-use types, (2) defining a set of characteristics of these land-use types, (3) quantifying these characteristics for all land-use types, (4) calculating the regional sum of each indicator for current land-use types to establish the baseline scenario, and (5) defining scenarios consisting of a set of goals to meet (maximize milk production or farm profit) and environmental constraints not to violate (per-ha limits on nitrate leaching, non-renewable energy use, and greenhouse gas emissions). Existing dairy farms were classified into 5 groups (from organic to intensive) according to their mode of production, quantity of milk production, and fodder-crop and grass area. Alternative land uses, namely 100%-grass-based dairy systems or forest, were characterized to explore the potential effects of replacing current dairy farmland with them. The MGLP model was unable to find a combination of current land-use types that could meet the three environmental constraints while using all of the land available. With alternative land-use types allowed, however, the model maximized milk production while meeting environmental constraints by allocating 55–60, 21–44, and 1–19% of the area to grass-based dairy systems, intensive farms, and forest, respectively, which decreased regional milk production by 8–30%. The trade-offs shown in MGLP results predict consequences of applying environmental constraints on agricultural production, revealing challenges that agricultural policies may face. The major benefits of coupling MGLP and LCA results include (1) taking into account social and economic indicators while considering environmental concerns, (2) quantification of potential environmental impacts to optimize agricultural production from an LCA perspective, (3) consideration of a variety of complementary production modes in a region, and (4) generation of scenarios that can be discussed with stakeholders as support information for environmentally-conscious decision making regarding land use.

Combining interactive multiple goal linear programming with an inter-stakeholder communication matrix to generate land use options

An Interactive Multiple Goal Linear Programming (IMGLP) model is developed that considers objectives of multiple stakeholders, i.e. different farmer groups, district agricultural officers and agricultural scientists for agricultural land use analysis. The analysis focuses on crop selection; considering irrigated and non-irrigated crops such as rice, sugarcane, sorghum, cotton, millet, pulses and groundnut. Interests of the most important stakeholders, farmers, policy makers and water users association are investigated. Important objectives of the farmers are increased income and retaining paddy area; of the policy makers (Agricultural Department) increased farmers' income, maintaining rural employment, improve water-use efficiency, reduce fertiliser and biocide use and discourage farmers from cultivating marginal lands; of the water users association optimising water use. Scenarios have been constructed by combining objectives and constraints. A Stakeholder Communication Matrix (SCM) indicating the level of communication and information flow among stakeholders in the district was generated after a Participatory Rural Appraisal (PRA). Results of the scenarios generated with the IMGLP model were compared with the matrix. The relevance of analysing the results of the scenarios generated with the IMGLP model in the context of the SCM is illustrated for a sample set of scenarios. Scenario 1 (S1), where both the paddy area and the agricultural area are retained at the current level, is preferred by the farmers. However, the Agricultural Department would identify more easily with S10 in which the paddy area is reduced by 50% and the agricultural area by 20%, in accordance with the policy of limiting the area of high water-demanding crops and dissuading farmers from cultivating marginal lands, while the water users association would prefer S12, where water use is minimised by expanding the area of crops that are relatively less water-demanding. Income in S12 is 22% lower than in S1, while water use is 36% lower, and there is a significant reduction in biocide use. The conflict between S1 and S10 is compounded by the fact that communication between small-scale farmers and the Agricultural Department is relatively weak. Analysing the scenarios in the context of the SCM is useful to gain insight into the interactions among stakeholders in the system and take curative measures if required for improved communication. While the IMGLP model considers the bio-economics of the land use system, the SCM describes its social aspects, which may be critical for successful implementation of the IMGLP model.

Combining farm and regional level modelling for Integrated Resource Management in East and South-east Asia

Currently, in many of the highly productive lowland areas of East and South-east Asia a trend to further intensification and diversification of agricultural land use can be observed. Growing economies and urbanization also increase the claims on land and water by non-agricultural uses. As a result, decisions related to the management and planning of scarce resources become increasingly complex. Technological innovations at the field/farm level are necessary but not sufficient – changes in resource use at regional scale will also be essential. To support decision-making in such situations, we advocate a multi-scale modelling approach embedded in a sound participatory process. To this end, the Integrated Resource Management and Land use Analysis (IRMLA) Project is developing an analytical framework and methods for resource use analysis and planning, for four sites in Asia. In the envisaged multi-scale approach, integration of results from field, farm, district and provincial level analysis is based on interactive multiple goal linear programming (IMGLP), farm household modelling (FHM), production ecological concepts and participatory techniques. The approach comprises the following steps: (i) inventory/quantification of current land use systems, resource availability, management practices and policy views, (ii) analysis of alternative, innovative land use systems/technologies, (iii) exploration of the opportunities and limitations to change resource use at regional scale under alternative future scenarios, (iv) modelling decision behaviour of farmers and identification of feasible policy interventions, and (v) synthesis of results from farm to regional level for negotiation of the most promising options by a stakeholder platform. In the current paper, the operationalisation of dual-scale analysis is illustrated by the outputs (development scenarios, promising policy measures and innovative production systems) from various component models for the case study Ilocos Norte, Philippines. An approach is discussed for the integration of results from the different model components at two different decision making levels (farm and province).

Multi-scale sustainability evaluation of natural resource management systems: Quantifying indicators for different scales of analysis and their trade-offs using linear programming

The purposes of this paper are: (a) to describe a framework designed for multi-scale sustainability evaluation of Natural Resource Management Systems (NRMS), and (b) to illustrate its application for quantitative analysis using linear programming. The framework described here is intended to contribute to the operationalisation of the concept of sustainability by supporting the processes of design, evaluation and implementation of alternative NRMS at different scales. In this paper, Linear Programming is used for the quantitative analysis of indicators and their trade-offs; using a schematised example, the basic characteristics of the Multi-scale Multiple Goal Linear Programming (M-MGLP) method are described. In M-MGLP, indicators pertaining to different scales of analysis can be set as objectives or constraints for the optimisation. In this way, stakeholders interacting in a specific region can be made aware of the consequences of alternative NRMS in terms of the different indicators at the same scale and/or for indicators at other scales of analysis. The paper ends with a discussion of the main strengths and limitations of the framework and, specifically, of linear programming.

Beyond adding up inputs and outputs: process assessment and upscaling in modelling nutrient flows

Departing from the historical background of scientific interest in soil fertility and sustainable agricultural production in sub-Saharan Africa, a review is conducted of nutrient budget studies carried out in semi-arid West Africa at scales ranging from individual fields to the sub-continent. For both, nitrogen and phosphorus, the comparison discloses largely diverging balances calculated for similar agro-ecosystems. In a first step, the modes of calculation of the nutrient budgets are examined. It is demonstrated that the calculations used in the different studies differ by the variables and biophysical processes taken into account, and by the choice of spatial scales as well as related time scales. One important discrepancy between approaches is whether and to which extent nutrient flows are internalized when upscaling. The extent to which the impact of individual and communal management, especially of pastoral and forestry resources, on nutrient flows is accounted for is a second cause of divergence. Moreover, it was observed that nutrient budgets tend to be increasingly negative as the spatial scale of the study increases from farm to sub-continent. This unexpected trend is traced back to the lack of internalization of nutrient flows when upscaling. The complexity of the scale patterns of nutrient flows and that of the interactions and the tradeoffs in the effects of management calls for the use of models to calculate nutrient budgets. Therefore, in a second step, examples of a static model, a multiple-goal linear programming model and a decision rules model were reviewed, all of which include the calculation of nutrient flows and balances and which were applied to West-African farming systems. The models are analyzed for their way of dealing with the critical issues of spatial and temporal scales and the impact of resource management on nutrient flows, taking into account that they have different objectives and were designed for different spatio-temporal scales. To conclude, suggestions were made for strengthening the use of models as tools enabling ex-ante testing of alternative agricultural technologies and policies that could improve soil nutrient balances in semi-arid sub-Saharan Africa.

Integration of Systems Network (SysNet) tools for regional land use scenario analysis in Asia

This paper introduces the approach of the Systems research Network (SysNet) for land use planning in tropical Asia with a focus on its main scientific–technical output: the development of the land use planning and analysis system (LUPAS) and its component models. These include crop simulation models, expert systems, GIS, and multiple goal linear programming (MGLP) models for land evaluation and optimization. LUPAS was designed as a decision support system (DSS) for strategic land use planning. Integration of LUPAS components in four case studies was performed in a network with national research teams and local stakeholders. This network allowed iterative evaluation and refinement of LUPAS for scenario analysis on technical and policy changes. Several interactive sessions with stakeholders led to more detail in scenarios (goals and constraints), model features and databases. To facilitate negotiation among stakeholders, the MGLP user interface (UI) was developed. In interactive sessions, goal restrictions are tightened to quantify trade-offs between conflicting goals. Choice and degree of tightening reflect the specific priorities for sustainable land use. The development of LUPAS is exemplified for one case study, Ilocos Norte, Philippines. Weak points of the system include inadequate spatial differentiation of socio-economic characteristics, scarce database for quantifying perennials and mixed cropping systems, and insufficient consideration of long-term effects of production technologies on resource quality. However, a promising perspective for effective policy support lies in the possible link of the regional LUPAS approach with farm household models.

A systems network (SysNet) approach for interactively evaluating strategic land use options at sub-national scale in South and South-east Asia

This paper presents SysNet, a systems research network in South and South-east Asia, established to develop and evaluate methodologies for enhancing formulation of strategic land use policies. SysNet adopted theory and concepts from both natural and social science approaches. Multiple goal linear programming was used to integrate information on a broad range of alternative land use systems, resource availability and policy objectives, to reveal possibilities and limitations of agricultural resource use and trade-offs between policy objectives. The methodology was developed and applied in and with a network of researchers and stakeholders, for four case study areas in India, Malaysia, the Philippines and Vietnam. An application is presented for Haryana State (India), to illustrate the methodology and its components, as well as the type of questions that can be explored and subsequently discussed with stakeholders. We discuss lessons learnt on how to communicate LUPAS to stakeholders in interactive settings, with details for the Kedah-Perlis case region in Malaysia.

A scenario exploration of strategic land use options for the Loess Plateau in northern China

Soil loss, food insecurity, population pressure and low income of the rural population are interrelated problems in the Loess Plateau of northern China, and result in a spiral of unsustainability. This paper examines Ansai County as a case study to explore strategic land use options that may meet well-defined goals of regional development, using a systems approach that integrated the fragmented and empirical information on the biophysical, agronomic and socio-economic conditions. We used production ecological principles, simulation modeling and multiple goal linear programming as integrative tools. Four scenarios were explored, representing major directions of agricultural development in the region and views of national and local stakeholders, farmers and environmentalists. The results indicate that soil conservation, food self-sufficiency and income for the rural population can be substantially improved by efficient resource use and appropriate inputs. In the long-term, terracing and use of crop rotations with alfalfa may be the best options for soil conservation. The large rural population and the lack of off-farm employment opportunities could be the most important factors affecting rural development in Ansai. This study contributes to the understanding of regional problems and agricultural development potentials, and shows agro-technical possibilities for alleviating the unsustainability problems in this fragile and poorly endowed region. To promote actual development towards the identified options, on-farm innovation and appropriate policy measures are needed. The explored land use options enable a much more targeted innovation and development of policies.

Modelling multiple objectives of land use for sustainable development

Sustainability is a human-centred concept that comprises multiple aspects and objectives of different interest groups. Sustainable development is not readily measurable, except as a compromise between different parts of society, of which some may try to represent future generations of mankind. To determine a sustainable development path in the relationship between agriculture and its natural environment, a profound knowledge of this complex system and its behaviour under different socio-economic conditions is necessary. We present a modelling system which consists of a set of hierarchically linked modules. These modules describe production activities in a way that allows an economic and ecological analysis of these techniques. The heart of the modelling system is a multiple goal linear programming model, which is generated by data base modules. Simulation of single farm models as well as regional models based on simultaneously optimised farm types is possible. The modelling system appears to be a highly flexible tool with respect to the number and type of farms, sites and production techniques. Environmental objectives can easily be included and different levels of goal achievement can be simulated. It is well suited for single farm analysis as well as for regional models, for static as well as dynamic approaches. It allows rapid adoption of the model and rapid calculation of scenarios. Therefore, it is suited for use in interactive environments with users which are interested in repeated runs with little changes in the goal function, prices, subsidies or technical coefficients. The results can be used for policy decisions as well as the strategic planning of individual farmers. Applications of the modelling system will be presented in following papers. In this paper the kind of information the model can generate and the circumstances of their usage are shown. ©

Sustainable land use in the Sudano-Sahelian zone of Mali: exploring economically viable options using multiple goal linear programming

Technical options in crop and animal husbandry to reduce soil nutrient mining and other forms of natural resource degradation in the Sudano-Sahelian zone should be economically attractive, if they are to be adopted. A model is presented in which agronomic and economic information and goals are combined to explore possibilities for agro-ecologically sustainable and economically viable land use in three different climatic regions in Mali and for a situation of non-degraded soils. The time frame of the study is to the year 2010. For each region, an agro-ecologically sustainable land use system (a combination of crop, livestock and pasture production systems) that maximizes income of the agricultural sector and satisfies self sufficiency targets is identified. Special attention is given to the use of chemical fertilizer in crop activities. It is shown that use of chemical fertilizer is an important element of sustainable and economically viable land use, especially in higher rainfall regions. Population size has a marked effect on optimal land use systems in the regions, but self sufficiency is not endangered even if the population is 50% higher than estimated for 2010. It is argued that results should not be used to simulate the actual situation or future developments, but to define priorities for agricultural development in the Sudano-Sahelian region.

APPLICATION OF MULTIPLE CRITERIA DECISION MAKING FOR THE DESIGN AND ANALYSIS OF GREENHOUSE CROPPING SYSTEMS

ISHS II Modelling Plant Growth, Environmental Control and Farm Management in Protected Cultivation APPLICATION OF MULTIPLE CRITERIA DECISION MAKING FOR THE DESIGN AND ANALYSIS OF GREENHOUSE CROPPING SYSTEMS

Operationalizing sustainability: exploring options for environmentally friendly flower bulb production systems

Current production systems for flower bulbs in the Netherlands employ considerable quantities of pesticides and nutrients per unit area. In 1993, an association of growers and environmentalists set out to design new farming systems that meet environmental objectives in addition to economic objectives. To support the design process, an explorative study was carried out to bring together the fragmented agronomic information and to assess agro-technical options for sustainable flower bulb production with a time horizon of 10 to 15 years. Crop and inter-crop management systems representing the agro-technical components of sustainability at the farm level, were generated with a computer model by systematically varying four system characteristics, three of which represented strategic and tactical aspects of crop protection. Subjective components, one economic and two environmental objectives and various socio-economic constraints, were identified in interaction with the stakeholders. Interactive multiple goal linear programming was used to optimize the objectives at the farm level and determine the exchange value of the economic objective in terms of the environmental objectives. Calculations were carried out for two reference farm types. The results revealed that the negative impact of environment-oriented production systems on farm gross margin is importantly mitigated by strategic choices at the farm level, such as renting land and allowing a soil health improving crop, even though of low gross margin, into the rotation. In contrast, the a priori attention of the growers was focused on improving tactical pest and nutrient management at the crop level, the effect of which on farm gross margin is constrained by the strategic choices. Sensitivity analyses highlighted the need for more insight into the ecology of soil-borne growth reducing factors and their effect on crop yield. The paper describes the approach used, reports results and discusses the usefulness of the approach for the stakeholders and for disciplinary crop protection research.

Aggregation of spatial units in linear programming models to explore land use options

Consequences of aggregating spatial units in an interactive multiple-goal linear programming (IMGLP) model are analysed for a schematized and an existing IMGLP model (GOAL) exploring land use options for the European Union. A discrimination was made between effects on objective functions for the system as a whole, and effects on related optimum land use allocation within the system. In GOAL, effects on land use allocation are more important than effects on the value of objective functions. Several rules or factors were identified that determine the effect of aggregation, among which the degree in curvilinearity in input-output relations and the method of aggregation are important ones. However, because of complicated interacting effects, the aggregation error is difficult to predict. Therefore, in land use studies using IMGLP it is important to first optimize the linear programming model at the non-aggregated level and then aggregate to the appropriate policy level. If aggregation is inevitable because LP models become too big, aggregation according to agro-ecological criteria, i.e., aggregation of units with similar output-input ratios and constraints, results in the smallest errors.

Assessment of future options for land use in the European Community

In the case of agricultural production, technical limitations can be used to explore future options for land use. As opposed to common economic outlooks this type of exploration provides information on the caveats and possibilities for agriculture. The options are calculated by combining a land evaluation (using a Geographical Information System, GIS), crop growth simulation models and Interactive Multiple Goal Linear Programming (IMGP). In the land evaluation, geographical information on soil types and other characteristics like steepness, stoniness, phase etc. is used to assess the suitability for different types of agriculture. Information on climate conditions and crop properties is used in the crop growth simulation models to calculate yield potentials for the suited areas. Economic, social and political goals are dealt with in a linear programming model. The result of this hierarchical modelling is a series of scenarios of optimal land use given the local properties of soils, crops and climate and given the economic, social and political considerations on topics like production costs, spreading of labor, market strategies and environmental conditions. Four different scenarios for future land use in the European Community emerge if the ongoing rise in productivity in agriculture is confronted with four partially conflicting goals of the Common Agricultural Policy (CAP). The scenarios present a picture of the end results in land use if one of these goals is taken to its logical conclusion. The goals are minimizing production costs (scenario Free market and free trade), maintaining regional employment (scenario Regional development), minimizing agricultural land use in favor of nature conservation (scenario Nature and landscape) and minimizing the stress on the environment due to pesticides and nutrients (scenario Environmental protection). All scenarios show results that are in sharp contrast with current opinions on the most probable developments in rural areas. In this paper the methodology will be exemplified and the results for possible land use in the EC will be discussed. Special attention is given to the interpretation of the results of this type of exploration.

Determination of input and output coefficients of cropping systems in the European Community

The Netherlands Scientific Council for Government Policy (WRR) has explored possible future developments in rural land use within the European Community (EC) to support strategic policy making. Multiple goal linear programming (MGLP) was applied to evaluate different scenarios based on alternative policy views. For the MGLP-model, WRR needed information on agricultural production systems, specifically quantification of inputs like nutrients, water, pesticides, labour and machinery, and outputs like crop yields and environmental pollution. In this paper, the determination of inputs and outputs is described for a number of pre-defined cropping systems at regional level, using results of a land evaluation study for the EC. All cropping systems defined are based on the assumption that the best available production techniques are being used, taking into account that the explorations aim at possible agricultural developments in the next 25 years.