Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non­ commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . ,. ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.

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I Introduction.- II Basic Concepts and Terminology.- III Methods for Multiple Objective Decision Making.- 1. Methods for No Articulation of Preference Information Given.- 1.1.1. Method of Global Criterion.- 2. Methods for a Priori Articulation of Preference Information Given.- 2.1. Methods for Cardinal Information Given.- 2.1.1. Utility Function Methods.- 2.1.2. Bounded Objective Methods.- 2.2. Methods for Mixed Ordinal and Cardinal Information Given.- 2.2.1. Lexicographic Method.- 2.2.2. Goal Programming.- 2.2.2a. Linear Goal Programming.- 2.2.2b. Nonlinear Goal Programming.- 2.2.3. Goal Attainment Method.- 3. Methods for Progressive Articulation of Preference Information Given (Interactive Methods).- 3.1. Methods for Explicit Trade-Off Information Given.- 3.1.1. Method of Geoffrion and Interactive Goal Programming.- 3.1.1 a. Method of Geoffrion.- 3.1.1b. Interactive Goal Programming (IGP).- 3.1.2. Surrogate Worth Trade-Off Method.- 3.1.3. Method of Satisfactory Goals.- 3.1.4. Method of Zionts-Wallenius.- 3.2. Methods for Implicit Trade-Off Information Given.- 3.2.1. STEM and Related Methods.- 3.2.2. SEMOPS and SIGMOP Methods.- 3.2.3. Method of Displaced Ideal.- 3.2.4. GPSTEM Method.- 3.2.5. Method of Steuer (Interactive MOLP Method).- 4. Methods for 'A Posteriori' Articulation of Preference Information Given.- 4.1.1. Parametric Method (Weighting Method).- 4.1.2. The ?-Constraint Method.- 4.1.3. MOLP Methods.- 4.1.4. Adaptive Search Method.- IV Applications.- 1. Academic Planning.- 2. Econometrics and Development Planning.- 3. Financial Planning.- 4. Health Care Planning.- 5. Land Use Planning for Community Development.- 6. Manpower Planning.- 7. Media Planning.- 8. Production Planning.- 9. Public Administration.- 10. Systems Reliability and Maintenance Policy.- 11. Transportation Planning and Traffic Management.- 12. Water Resources Management.- V Concluding Remarks.- VI Bibliography.- Books, Monographs, and Conference Proceedings.- Journal Articles, Technical Reports, and Theses.