Shyamal Sen

A Linear Goal Programming Procedure for Academic Personel Management Problems in University System

This article describes a goal programming (GP) procedure for proper allocation of teaching personnel to the teaching departments for smooth functioning of the academic activities of a university. In the academic resource planning context, both the crisp and fuzzy goal objectives which are frequently involved with the problem are discussed. Again, certain ratios in the fractional forms which are inherently associated to the problem are also taken into consideration. In the model formulation, achievement of the highest membership value (unity) of the membership functions of the defined fuzzy goal as well as attainment of the prescribed goal levels of the crisp goals to the extent possible are considered. In the solution process, the fractional goals are transformed into the linear goals by using the linear transformation approach studied previously. A case study of University of Kalyani, West Bengal, India is considered to expound the potential use of the proposed model.

A Goal Programming Procedure for Solving Interval Valued Multiobjective Fractional Programming Problems

This article presents a goal programming (GP) procedure for solving interval valued multiobjective fractional programming problems (MOFPPs) with interval objective functions in an inexact environment. In the proposed approach, the interval objective functions are first converted into the standard objective goals in the fractional GP formulation by using the interval arithmetic technique. Then, in the decision process, the fractional goals are transformed into the linear goals by linearization approach by B.B. Pal et al (2008) studied previously. In solution process, the executable GP model of the problem is formulated with the objective to minimize the regret with the view to achieve the goals in their specified ranges and thereby arriving at a most satisfactory solution in the decision making environment. Two numerical examples are solved to illustrate the proposed approach and the model solution of one problem is compared with the solution of a fuzzy programming approach by B.B. Pal et al. (2008) studied previously.

A linear Goal Programming approach to multiobjective fractional programming with interval parameter sets

This paper presents a Goal Programming (GP) approach to solving multiobjective fractional programming problems (MOFPPs) involving interval coefficients and target intervals. In the proposed approach, interval-valued fractional objectives are converted into the standard fractional objective goals in GP formulation. The fractional goals are then transformed into linear goals within the framework of GP by using the linear transformation approach. In the GP model formulation, the goal achievement function for minimising the lower bounds of the necessary regret intervals of the goal objectives for the defined interval parameter sets from the optimistic point of view is taken into consideration. In the solution process, the mixed 0-1 method is used to overcome the computational complexity arises for non-convex in nature of the formulated model of the problem. Two numerical examples are provided to illustrate the solution approach.

A priority-based goal programming method for solving academic personnel planning problems with interval-valued resource goals in university management system

This paper describes a goal programming (GP) procedure for modelling and solving academic resource planning problems in university management system. In the academic resource planning context, certain objectives having the characteristics of fractional programming problems are considered as interval-valued goals to make a satisfactory decision regarding staff allocation for smooth functioning of the academic activities of the departments. In the proposed approach, the interval-valued goals are first converted into the standard goals by using interval arithmetic technique. Then, the fractional goals are transformed into linear goals by using linearisation approach to solve the problem by employing linear GP methodology. In the model formulation of the problem, both the aspects of GP, minsum and minimax approaches, are addressed to construct the goal achievement function for minimising the possible regret towards achieving the goal values within the target intervals specified by the decision maker (DM) in the decision making environment. A demonstrative case example of the University of Kalyani, West Bengal (W.B.), India is considered to expound the proposed model.

Using Fuzzy Goal Programming for Long-Term Water Resource Allocation Planning in Agricultural System: A Case Study

This paper presents a fuzzy goal programming (FGP) method for modeling and solving farm planning problems for optimal production of several crops by proper allocation of irrigation water in different seasons in a planning year. In the model formulation, the priority based FGP is addressed for achievement of the highest value (unity) of the membership goals defined for the fuzzy goals of the problem to the extent possible on the basis of needs and desires of the decision maker (DM) in the decision making situation.

A linear fuzzy goal programming approach for solving patrol manpower deployment planning problems — A case study

This paper demonstrates a fuzzy goal programming (FGP) procedure for modeling and solving patrol manpower deployment problems of Metropolitan cities to deterring traffic violations and accidents and thereby reducing accident rate in a traffic control planning horizon.

A priority based interval-valued Goal Programming approach for land utilization planning in agricultural system: A case study

This paper demonstrates a Goal Programming (GP) Procedure for modeling and solving land utilization planning problems having interval-valued objective goals for optimal production of seasonal crops in agricultural system. In the proposed approach, utilization of total land for cultivation, aspiration levels of production of crops, expected profit from the farm as well as certain ratios of crops production and profit achievement are described interval-valued for goal achievement in the context of making proper cropping plan. In the model formulation of the problem, the defined interval-valued goals are converted into conventional goals by using interval arithmetic technique in interval programming (IP) and introducing under- and over-deviational variables to each of them. Again, certain ratio goals which are inherent to the problem are transformed into linear goals by employing the linear transformation approach to solve the problem by using the linear GP methodology. In the decision process, both the minsum GP and minmax GP approaches are addressed in the achievement function for minimizing the possible regret towards goal achievement from the optimistic point of view in the inexact decision making environment. The potential use of the approach demonstrated via a case example of the Nadia District, West Bengal (W.B), INDIA.

The Use of Chance Constrained Fuzzy Goal Programming for Long-Range Land Allocation Planning in Agricultural System

This paper describes how the fuzzy goal programming (FGP) can be efficiently used for modelling and solving land allocation problems having chance constraints for optimal production of seasonal crops in agricultural system.

A fuzzy goal programming approach for solving multiobjective fuzzy stochastic programming problems

This article presents a fuzzy goal programming (FGP) procedure for solving a stochastic multiobjective decision making (MODM) problem having the finite probabilistic aspiration levels for achievement of the chance constrained goals.

Interval Goal Programming Approach to Multiobjective Programming Problems with Fuzzy Data Uncertainty

This paper presents interval goal programming approach for solving multiobjective programming problems with fuzzy parameter sets. In the proposed approach, the notion of interval approximation technique to fuzzy numbers is used to transform the objectives with interval parameter sets. In the model formulation, interval arithmetic is employed to convert the problem into the standard goal programming problem. In goal achievement function, both the modelling aspects in goal programming (GP), minsum GP and minmax GP are taken into account as a convex combination of them to minimize possible deviations from specified target intervals for goal achievements from optimistic point of view of decision maker (DM) in the decision situation. A numerical example is solved to illustrate the proposed approach.