A Genetic Algorithm Based Goal Programming Method for Solving Patrol Manpower Deployment Planning Problems with Interval-Valued Resource Goals in Traffic Management System: A Case Study

摘要

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 goals in GP approach by using interval arithmetic technique. Then, the defined goals are transformed into the conventional form of goals by introducing under- and over-deviational variables to each of them to make a reasonable balance of decision in the deployment planning context. In the achievement function of the executable GP model, both the minsum and minntax aspects of GP are addressed to construct the achievement function for minimizing the possible regret towards achieving the goal values from the optimistic point of view in the decision making environment. A demonstrative example of the city Kolkata, West Bengal, India is solved and the model solution is compared with the solution of conventional GP approach [1] studied previously.