Fractional programming is presented as a tool for studying the sustainability of agricultural systems. The essentials of the technique in both the single and the multi-objective cases are outlined. The lack of friendl...
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Fractional programming is presented as a tool for studying the sustainability of agricultural systems. The essentials of the technique in both the single and the multi-objective cases are outlined. The lack of friendly algorithms embedded in programming packages to solve the models is a shortcoming for the extensive use of a technique well adapted to represent many problems in economics. Two procedures for avoiding this shortcoming in the multiple objective case are discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.
We consider a model for data envelopment analysis with infinitely many decisionmaking units. The determination of the relative efficiency of a given decision-making unit amounts to the solution of a semi-infinite opti...
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We consider a model for data envelopment analysis with infinitely many decisionmaking units. The determination of the relative efficiency of a given decision-making unit amounts to the solution of a semi-infinite optimization problem. We show that a decision-making unit of maximal relative efficiency exists and that it is 100% efficient. Moreover, this decision-making unit can be found by calculating a zero of the semiinfinite constraint function. For the latter task we propose a hi-level algorithm. We apply this algorithm to a problem from chemical engineering and present numerical results.
This paper designed and developed a multi-objective programming (MOP) model to illustrate the dynamic relationship among technologies, productive activities, constraints and farmers' objectives in the peri-urban v...
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This paper designed and developed a multi-objective programming (MOP) model to illustrate the dynamic relationship among technologies, productive activities, constraints and farmers' objectives in the peri-urban vegetable production system and use the model as an economic tool in analysing probable consequences of a given action or innovation on the farm. The best compromise solution was generated using four analytical steps, as follows: single-objective optimization (to determine the ideal and anti-ideal values of the objective functions);constrained optimization (to generate the set of Pareto non-dominated solutions);cluster analysis (to trim down efficient set into smaller homogeneous groups);and compromise programming (to determine where the best compromise solution lies). The study then evaluated the income and risk impacts of technological innovation, specifically that of the technologies espoused by the AVRDC-Manila Peri-urban project for tomato and pak choi production during the hot-wet season. It was found that relative to the current production system, the entry of grafted tomato under rainshelter in the best compromise solution could increase farmer's income, however, the price-induced risk also increased. This effect was brought about by the increased yield of tomato that caused variance of income to increase. This result indicates that under existing conditions, the higher income offered by the costly technology will only be acceptable if farmers are willing to take on the higher risk. The MOP model also assessed how making capital more accessible to the farmers will affect the extent of adoption (proxied by area planted to the crop) of the technology. Results showed that income would increase when capital constraint was relaxed. This increase in income, however, was made possible largely by the change in crop mix, with a relatively small increase in area planted to tomato. With regard the level of risk, the change in production resulted in an increase
Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose a mathe...
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Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose a mathematical programming approach for the evaluation and selection of shipbrokers. Specifically, the score of each ship broker is a composite measure that is derived by aggregating a set of performance criteria, e.g., reputation, etc. The developed mathematical programming models enable the aggregation and weighting of the criteria. We employ three optimization models to explore the effect of different weighting schemes on the scores and ranking of the shipbrokers. The models that provide a common set of weights for all the shipbrokers establish the appropriate ground for comparisons among them. Also, our models facilitate the incorporation of user priorities over the criteria in the form of weight restrictions. The proposed approach is illustrated by assessing seven shipbroker offers for selling a dry-bulk ship using four criteria, namely revenue, brokerage fee, brokerage time and terms & conditions.
In this paper it is shown that a relaxation defining the class of generalized d-V-type-I functions leads to a new class of multi-objective problems which preserves the sufficient optimality and duality results in the ...
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In this paper it is shown that a relaxation defining the class of generalized d-V-type-I functions leads to a new class of multi-objective problems which preserves the sufficient optimality and duality results in the scalar non-differentiable case, and avoids the major difficulty of verifying that the inequality holds for the same kernel function. The results obtained in this paper generalize and extend the previously known results in this area. (c) 2005 Elsevier Inc. All rights reserved.
Maximum entropy algorithm for approximating multi-objective smoothless semi-infinite programming is presented. The convergence of the approximating algorithm is obtained in general from the convergence of the series o...
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Maximum entropy algorithm for approximating multi-objective smoothless semi-infinite programming is presented. The convergence of the approximating algorithm is obtained in general from the convergence of the series of entropy functions (such as variational convergence).
This note is a contribution to the on-going debate about the merits and demerits of goal programming. We concentrate on the special case of integer goal programming. Examples show that the approach is questionable, es...
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This note is a contribution to the on-going debate about the merits and demerits of goal programming. We concentrate on the special case of integer goal programming. Examples show that the approach is questionable, especially if used in connection with a standard branch-and-bound-based solution technique.
In this paper, we have introduced a new class of (phi,d)-V-type I univex, quasi (phi,d)-V- type I univex, pseudo (phi,d)-V-type I univex, quasi-pseudo (phi,d)-V-type I univex and pseudo-quasi (phi,d)-V-type I univex f...
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In this paper, we have introduced a new class of (phi,d)-V-type I univex, quasi (phi,d)-V- type I univex, pseudo (phi,d)-V-type I univex, quasi-pseudo (phi,d)-V-type I univex and pseudo-quasi (phi,d)-V-type I univex functions in case of nonlinear multiobjectiveprogramming problem where functions involved are nondifferentiable and illustrated through non- trivial examples that this class extends some known classes in literature. Various Karush-Kuhn-Tucker type sufficient optimality conditions are obtained under this newly introduced class of functions. Also, for mixed type multiobjective dual program, we have established weak, strong, converse and strict converse duality results in order to relate the efficient and weak efficient solutions of primal and dual problem.
The paper treats the multi-objective programming problem with a large composite set of (linear and nonlinear) objective functions, the domain of feasible solutions being defined by a set of linear equalities/inequalit...
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ISBN:
(纸本)9783642184659
The paper treats the multi-objective programming problem with a large composite set of (linear and nonlinear) objective functions, the domain of feasible solutions being defined by a set of linear equalities/inequalities representing a large scale problem. One constructs a preferred solution i.e. a non-dominated solution chosen via extending the decision-making framework. A feasible approach, for this class of problems, is to use a solver for the Linear programming problems and a solver for multiple Attribute Decision Making problems in combination with Parallel and Distributed Computing techniques based on a GRID configuration.
This study presents a novel means of resolving multiple objective goal programming (GP) problems with quasi-convex linear penalty functions. The proposed method initially expresses a quasi-convex function by the maxim...
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