Multi-criteria branch and bound: A vector maximization algorithm for Mixed 0-1 Multiple Objective Linear Programming G. Mavrotas * , D. Diakoulaki Laboratory of Industrial and Energy Economics, National Technical University of Athens, Department of Chemical Engineering, Div. II, Zografou Campus, Athens 15780, Greece Abstract The paper describes the Multi-Criteria Branch and Bound (MCBB) algorithm, a vec- tor maximization algorithm capable of deriving all efficient extreme points, for small- and medium-sized Mixed 0-1 Multiple Objective Linear Programming (Mixed 0-1 MOLP). Particular emphasis is given to computational aspects aiming principally at accelerating the solution procedure. For facilitating the decision makerÕs search toward the most preferred efficient solution, the notion of efficient combinations of the binary variables is further exploited. It is also shown that the MCBB algorithm can be used in single objective problems (Mixed Integer LP problems) in order to determine all alter- native optima, as well as in Mixed Integer MOLP problems and Pure 0-1 MOLP prob- lems that frequently arise in practice. A computational experiment is included in the paper in order to illustrate the performance of the algorithm. Ó 2005 Elsevier Inc. All rights reserved. Keywords: Multiple objective programming; Mixed integer programming; Branch and bound 0096-3003/$ - see front matter Ó 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.amc.2005.01.038 * Corresponding author. E-mail address: mavrotas@chemeng.ntua.gr (G. Mavrotas). Applied Mathematics and Computation 171 (2005) 53–71 www.elsevier.com/locate/amc