Application of genetic algorithm for scheduling and schedule coordination problems

The problems on scheduling and schedule co‐ordination usually have conflicting objectives related to user's cost and operator's cost. Users want to spend less time to wait, transfer and travel by public buses. Operators are interested in profit making by lesser vehicle operating cost and having a minimum number of buses. As far as level of service is concerned users are interested in lesser crowing while operators are concerned with maximizing profit and thus to have higher load factors. In schedule co‐ordination problems transfer time plays an important role. Users are interested in coordinating services with in acceptable waiting time whereas operators prefer to have lesser services and want to meet higher demands, which invariably increases waiting time. These problems have multiple conflicting objectives and constraints. It is difficult to determine optimum solution for such problems with the help of conventional approaches. It is found that Genetic Algorithm performs well for such multi objective problems.