Annals of Operations Research 63(1996)397-414 397 A combined branch-and-bound and genetic algorithm based approach for a flowshop scheduling problem Amit Nagar School of Business, University of Windsor, Windsor, Ontario, Canada Sunderesh S. Heragu and Jorge Haddock Decision Sciences and Engineering Systems Department, Rensselaer Polytechnic Institute, Troy, NY 12180, USA In this paper, we study the applicationof a meta-heuristicto a two-machineflowshop scheduling problem. The meta-heuristicuses a branch-and-boundprocedure to generate some information, which in turn is used to guide a genetic algorithm's search for optimal and near-optimal solutions. The criteria considered are makespan and average job flowtime. The problem has applications in flowshop environmentswhere management is interested in reducing turn-around and job idle times simultaneously. We develop the combined branch-and-bound and genetic algorithm based procedure and two modified versions of it. Their performanceis compared with that of three algorithms: pure branch- and-bound, pure genetic algorithm,and a heuristic.The results indicatethat the combined approach and its modified versions are better than either of the pure strategies as well as the heuristic algorithm. Keywords: Genetic algorithm, scheduling, branch-and-bound. 1. Introduction and brief literature review We study a two-machine bicriteria flowshop scheduling problem in which the objective is to minimize the weighted sum of schedule makespan and average job flowtime. The problem has applications in industries where each job must undergo two basic processes in the same sequence. For example, in the steel industry, each job undergoes wire-drawing first and annealing next. At the aggregate planning or macro level in general manufacturing industries, each job must undergo fabrication first and assembly next. The two-machine bicriteria flowshop scheduling problem has been studied in [1-3]. All the previous approaches to this problem have relied on conventional optimization techniques such as goal programming and branch-and- bound. Selen and Hott [ 1] developed a goal programming formulation for the bicriteria © J.C. Baltzer AG, Science Publishers