In this paper, a solution procedure has been given for the Chance Constrained Programming Models For Multi-Objective Interval Solid Transportation Problem under stochastic environment (MOISTP) where the cost coefficients of the objective functions, the source availability, destination demand and conveyance capacities have been taken as stochastic intervals by the decision makers. The problem has been transformed into a classical multi-objective transportation problem where the multiple objective functions are minimized by using fuzzy programming approach. Numerical examples are provided to illustrate the approach

In this paper, a new concept of anti-homomorphism between two fuzzy groups G and G is defined many results analogous to homomorphism of groups are established KEYWORDS Fuzzy set, fuzzy level subset, fuzzy groups, fuzzy level subgroup, fuzzy normal subgroup, fuzzy abelian subgroup, fuzzy cyclic subgroup homomorphism, Anti-homomorphism, Anti-automorphism.

To minimize the computational effort needed in solving a Integer Linear Fractional programming problem a new approach has been proposed. Here we use  matrix for finding the solution of the integer linear fractional programming problems.

In this paper, a solution procedure has been given for the Multi-Objective Interval Solid Transportation Problem under stochastic environment where the cost coefficients of the objective functions, source availability, destination demand and conveyance capacities have been taken as stochastic intervals. The problem has been transformed into a classical multi-objective transportation problem where the multiple objective functions are minimized by using fuzzy programming approach. Numerical examples are provided to illustrate the approach.

In this paper, a solution procedure has been given for the Multi-Objective Interval Solid Transportation Problem under stochastic environment where the cost coefficients of the objective functions have been taken as random variables whereas the source availability, destination demand and conveyance capacities have been taken as stochastic intervals by the decision makers. The problem has been transformed into a classical multi-objective transportation problem where the multiple objective functions are minimized by using fuzzy programming approach. Numerical examples are provided to illustrate the approach.