Insecticidal and repellant activities of Southeast Asia plants towards insect pests: a review

Crops are being damaged by several plant pests. Several strategies have been developed to restrict the damage of cultivated plants by using synthetic pesticides and repellants. However, the use to control these insects is highly discouraged because of their risks on humans. Therefore, several alternatives have been developed from plant extracts to protect crops from plant pests. Accordingly, this review focuses on outlining the insecticidal and repellant activities of Southeast Asia plants towards insect pests. Several extracts of plants from Southeast Asia were investigated to explore their insecticidal and repellant activities. Azadiracha indica (neem) and Piper species were highly considered for their insecticidal and repellant activities compared to other plants. This review also addressed the investigation on extracts of other plant species that were reported to exert insecticidal and repellant activities. Most of the conducted studies have been still in the primarily stage of investigation, lacking a focus on the insecticidal and repellant spectrum and the identification of the active constituents which are responsible for the insecticidal and repellant activity

Information and decision in optimal inventory processes

AbstractAccording to developments in management information systems, more investigation is required to adapt the fundamental features that American management information systems have to the Japanese technical climate. One important problem is to decide the kind and the accuracy of management information systems. If complete information is desired regarding a system in each stage of control, some time and cost will be entailed. Otherwise, if with incomplete information a decision is quickly made, we must put up with using a probability that controls a non-optimum system. We do not have the complete accuracy for both the information and decision. This is analogous to Heisenberg's uncertainty principle. In this paper, we discuss the relation between the information and decision in optimal inventory processes from this viewpoint

A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection

Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers

Improved two-phase solution strategy for multiobjective fuzzy stochastic linear programming problems with uncertain probability distribution

Multiobjective Fuzzy Stochastic Linear Programming (MFSLP) problem where the linear inequalities on the probability are fuzzy is called a Multiobjective Fuzzy Stochastic Linear Programming problem with Fuzzy Linear Partial Information on Probability Distribution (MFSLPPFI). The uncertainty presents unique difficulties in constrained optimization problems owing to the presence of conflicting goals and randomness surrounding the data. Most existing solution techniques for MFSLPPFI problems rely heavily on the expectation optimization model, the variance minimization model, the probability maximization model, pessimistic/optimistic values and compromise solution under partial uncertainty of random parameters. Although these approaches recognize the fact that the interval values for probability distribution have important significance, nevertheless they are restricted by the upper and lower limitations of probability distribution and neglected the interior values. This limitation motivated us to search for more efficient strategies for MFSLPPFI which address both the fuzziness of the probability distributions, and the fuzziness and randomness of the parameters. The proposed strategy consists two phases: fuzzy transformation and stochastic transformation. First, ranking function is used to transform the MFSLPPFI to Multiobjective Stochastic Linear Programming Problem with Fuzzy Linear Partial Information on Probability Distribution (MSLPPFI). The problem is then transformed to its corresponding Multiobjective Linear Programming (MLP) problem by using a-cut technique of uncertain probability distribution and linguistic hedges. In addition, Chance Constraint Programming (CCP), and expectation of random coefficients are applied to the constraints and the objectives respectively. Finally, the MLP problem is converted to a single-objective Linear Programming (LP) problem via an Adaptive Arithmetic Average Method (AAAM), and then solved by using simplex method. The algorithm used to obtain the solution requires fewer iterations and faster generation of results compared to existing solutions. Three realistic examples are tested which show that the approach used in this study is efficient in solving the MFSLPPFI

Evaluation of SCOR KPIs using a predictive MILP model under fuzzy parameters.

The Supply Chain Operations Reference (SCOR) model is a well-recognized process reference model in the supply chain management field. Based on the literature, there is no research work that proposes a method to estimate and predict SCOR key performance indicators (KPIs) of a company. The objective of this paper is to propose a methodology to assess the SCOR KPIs under uncertainties based on level 2 of the SCOR-Make process metric, including nine KPIs. The proposed methodology consists of predictive MILP models with fuzzy parameters and some algorithms to assess the KPIs related to agility. A case study of a bottled-water factory is conducted to demonstrate the application of the proposed methodology. From the fact that some parameters are fuzzy numbers, the obtained SCOR KPIs are fuzzy numbers, which provide more information than constant values. The findings indicate that the proposed methodology is capable of developing the relationship between the manufacturing parameters and the SCOR KPIs, which enable the effective prediction process especially when the manufacturing parameters are changed or improved

A fuzzy risk approach for performance evaluation of an irrigation reservoir system

Abstract In this paper, a model for fuzzy risk of low yield of a crop is developed to study the implications of a reservoir operating policy model. When an optimal operating policy is derived based on a known objective, the policy itself does not, in general, indicate a measure of the system performance unless a criterion to this effect is embedded in the objective function. While a systems analyst is interested in the nature of the objective function used in arriving at a policy, the irrigation decision maker would look for the implications of using the policy through answers to the questions such as, how often the system will fail and how quickly it will recover from a failure. It is, therefore, important that the implications of reservoir operation with a given policy be studied keeping in view the interests of the decision makers. Some earlier studies on reservoir operation models for irrigation have considered reliability, resiliency and productivity index, as the performance indicators of the operating policy. In this paper, fuzzy risk of low yield of a crop is considered as another performance indicator to address uncertainties due to both randomness and fuzziness. Uncertainty due to randomness arises primarily because of the random variations of hydrologic variables such as reservoir inflows and rainfall in the command area. Uncertainty due to imprecision or fuzziness arises because of uncertain crop yield response to various factors (such as farm practices and climatic variables) other than to the applied water. Two important concepts are introduced in this paper with respect to irrigation reservoir system. The first one is related to viewing the low yield of a crop, as a fuzzy event. The second concept is related to the definition of fuzzy risk of low yield of a crop. The fuzzy risk of low yield is derived using the concept of probability of a fuzzy event. G(k, i, l, M, p, t) system performance measure corresponding to storage class interval k in period t and l in period t + 1, inflow class i, rainfall class p and soil moisture vector M in period t i class interval to which the inflow in period t belongs j class interval to which the inflow in period t + 1 belongs k class interval to which storage at the beginning of period t belongs l class interval to which storage at the beginning of period t + 1 belongs l * optimal value of l l * (k, i, p, M, t) optimal end of period storage, for a given initial storage class interval k, inflow class interval i, rainfall class interval p, and initial soil moisture vector of demand from crop c in period t ER t effective rainfall in period t ET t ac actual evapotranspiration of crop c in period t ET t pc potential evapotranspiration of a crop c in period t F c farm practices for crop c FETDM fuzzy evapotranspiration deficit model crisp set of low relative yield of a crop c m c class interval to which soil moisture of crop c at the beginning of period t belongs M soil moisture vector in period t, m 1 , . . . , m NC , representing the initial soil moisture class intervals of crops in period t M = {m 1 , . . . , m NC } soil moisture vector representing the soil moisture class intervals of crops in period t nk class interval to which the relative yield of a crop belongs NC number of crops NC t number of crops in time period t p class interval to which the rainfall in period t belongs P probability of a fuzzy event P t ij probability that the inflow Q t+1 in time period t + 1 is in class interval j, given the inflow Q t in time period t is in class interval i K.R. Suresh, P.P. Mujumdar / Agricultural Water Management 69 (2004

Optimisation problems as decision problems: The case of fuzzy optimisation problems

The importance that decision-making problems and optimisation problems have today in all aspects of life is beyond all doubt. Despite that importance, both problems tend to be thought of as following different routes, when they have, in fact, a “symbiotic” relation. Here, we consider the different decision problems that arise when different kinds of information and framework of behaviour are considered, and we explore the corresponding optimisation problems that can be derived for searching the best possible decision. We explore the case where Fuzzy Mathematical Programming problems are obtained as well as other new ones in the fuzzy context.Research supported by the project TIN2014-55024-P from the Spanish Govern as well as by the project TIC-8001 from the Andalusian Govern (both financed with FEDER funds)

Efficiency in South African agriculture : a two-stage fuzzy approach

PURPOSE : The purpose of this paper is to assess the efficiency of agricultural production in South Africa from 1970 to 2014, using an integrated two-stage fuzzy approach. DESIGN/METHODOLOGY/APPROACH : Fuzzy technique for order preference by similarity to ideal solution is used to assess the relative efficiency of agriculture in South Africa over the course of the years in the first stage. In the second stage, fuzzy regressions based on different rule-based systems are used to predict the impact of socio-economic and demographic variables on agricultural efficiency. They are compared with the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2016a). FINDINGS : The results show that the fuzzy efficiency estimates ranged from 0.40 to 0.68 implying inefficiency in South African agriculture. The results further reveal that research and development, land quality, health expenditure–population growth ratio have a significant, positive impact on efficiency levels, besides the GINI index. In terms of accuracy, fuzzy regressions outperformed the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2015). PRACTICAL IMPLICATIONS : Policies to increase social expenditure especially in terms of health and hence productivity should be prioritized. Also policies aimed at conserving the environment and hence the quality of land is needed. ORIGINALITY/VALUE : The paper is original and has not been previously published elsewhere.https://www.emerald.com/insight/publication/issn/1463-5771hj2019Economic