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This paper proposes a modeling of data networks with delay, packet loss ratio and network cost and an optimization of them using genetic algorithm. The network delay is expressed in terms of three delays such as propagation delay, transmission delay and queuing delay of links. The packet loss ratio is defined as the ratio of successful packet transmission to total transmission over a link and the...
This article demonstrates how the GA approach can be efficiently used to the penalty function based fuzzy goal programming (FGP) formulation of academic personnel planning problems in university management system. In the proposed approach, requirement of total full-time teaching staff and allocation of pay-roll budget to each of academic departments are fuzzily described. The recruitment of minimum...
This paper presents how the fuzzy goal programming (FGP) and interval valued goal programming (IVGP) can be efficiently used for modelling and solving land allocation problems for optimal production of seasonal crops in agricultural system. In the proposed approach, utilization of cultivable land, production of crops and target level of profit are fuzzily described. The supply and utilization of productive...
This article demonstrates how the genetic algorithm (GA) method can be used to solve interval-valued goal programming (GP) model of patrol manpower allocation problem to various road-segment areas in different shifting times of Metropolitan cities to deter traffic violations and accidents. In the model formulation of the problem, the goals with target intervals are first converted into the standard...
In this article, a genetic algorithm (GA) based fuzzy goal programming (FGP) procedure for solving bilevel programming problems (BLPPs) having the chance constraints in large hierarchical decision problems is presented. In the proposed approach, first the chance constraints are converted into their deterministic equivalent in the decision making environment. In the model formulation of the problem,...
This paper presents how genetic algorithm (GA) can be used in fuzzy goal programming (FGP) formulation of multiobjective stochastic programming (SP) problems. In the proposed approach, the individual optimal decision of each of the objectives are determined by using the GA scheme adopted in the process of solving the problem after converting the chance constraints into their deterministic equivalent...
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