A method, apparatus and product for automated multi-objective solution selection. The method comprises obtaining a set of solutions to a multi-objective problem, wherein each solution is a non-dominated solution. The method further comprises computing outranking weights for each pair of solutions and selecting a subset of the set of solutions based upon a defensive criteria in with respect to the outranking weights, wherein the defensive criteria relates to a number of solutions that outrank the subset. The method further comprises outputting the subset of the set of solutions
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computerized apparatus having a processor, the processor being adapted to perform the steps of: obtaining a set of solutions to a multi-objective problem, wherein each solution is a non-dominated solution; computing outranking weights for each pair of solutions; selecting a subset of the set of solutions based upon a defensive criteria in with respect to the outranking weights, wherein the defensive criteria relates to a number of solutions that outrank the subset; and outputting the subset of the set of solutions. 2. The computerized apparatus of claim 1, wherein the processor being adapted to perform: selecting a second subset of the set of solutions based upon an offensive criteria with respect to the outranking weights, wherein the offensive criteria relates to a number of solutions that the subset outranks. 3. The computerized apparatus of claim 2, wherein the processor being adapted to perform: selecting between using the defensive criteria and the offensive criteria based on a risk preference of a user. 4. The computerized apparatus of claim 3, wherein the risk preference is either a loss aversion risk preference or a gain prone risk preference. 5. The computer-implemented method of claim 1, wherein the outranking weight is computed by a following formula: 1 min k  ( f i  ≺ k  f j ) , where fi is the first solution, fj is the second solution, and k is a k-domination relation. 6. The computer-implemented method of claim 1, wherein the outranking weight is computed by a following formula: max k  ( f i  ≺ k  f j ) , where fi is the first solution, fj is the second solution, and k is a k-domination relation. 7. The computer-implemented method of claim 1, wherein the outranking weight is computed by a following formula: σ(fi, fj), where fi is the first solution, fj is the second solution, and σ( ) is a credibility index that is based on a concordance value and on discordance indexes. 8. The computer-implemented method of claim 1, wherein said selecting the subset is performed by solving a following linear programming problem: minimize t, subject to: ∑ v   sol  [ v ] ≥ N rec and subject to: ∑ v    w  ( u , v ) · sol  [ v ] ≤ t   ∀ u , wherein Nrec is a predetermined maximal size of the subset, wherein w(u,v) is a weight between solutions u and v, wherein sol[v] is a binary decision variable indicating whether solution v is a member of the subset. 9. The computerized apparatus of claim 1, wherein the processor being adapted to perform: partitioning the set of solutions into a plurality of partitions, wherein said computing and said selecting are performed several times, each time with respect to a different partition. 10. A method comprising: obtaining a set of solutions to a multi-objective problem, wherein each solution is a non-dominated solution; computing, by a processor, outranking weights for each pair of solutions; selecting a subset of the set of solutions based upon a defensive criteria in with respect to the outranking weights, wherein the defensive criteria relates to a number of solutions that outrank the subset; and outputting the subset of the set of solutions. 11. The method of claim 10 further comprising: selecting a second subset of the set of solutions based upon an offensive criteria with respect to the outranking weights, wherein the offensive criteria relates to a number of solutions that the subset outranks. 12. The method of claim 11, further comprising selecting between using the defensive criteria and the offensive criteria based on a risk preference of a user. 13. The method of claim 12, wherein the risk preference is either a loss aversion risk preference or a gain prone risk preference. 14. The method of claim 10, wherein the outranking weight is computed by a following formula: 1 min k  ( f i  ≺ k  f j ) , where fi is the first solution, fj is the second solution, and k is a k-domination relation. 15. The method of claim 10, wherein the outranking weight is computed by a following formula: max k  ( f i  ≺ k  f j ) , where fi is the first solution, fj is the second solution, and k is a k-domination relation. 16. The method of claim 10, wherein the outranking weight is computed by a following formula: σ(fi, fj), where fi is the first solution, fj is the second solution, and σ( ) is a credibility index that is based on a concordance value and on discordance indexes. 17. The method of claim 10, wherein said selecting the subset is performed by solving a following linear programming problem: minimize t, subject to: ∑ v   sol  [ v ] ≥ N rec and subject to: ∑ v    w  ( u , v ) · sol  [ v ] ≤ t   ∀ u , wherein Nrec is a predetermined maximal size of the subset, wherein w(u,v) is a weight between solutions u and v, wherein sol[v] is a binary decision variable indicating whether solution v is a member of the subset. 18. The method of claim 10 further comprising partitioning the set of solutions into a plurality of partitions, wherein said computing and said selecting are performed several times, each time with respect to a different partition. 19. A computer program product comprising a computer readable storage medium retaining program instructions, which program instructions when read by a processor, cause the processor to perform a method comprising: obtaining a set of solutions to a multi-objective problem, wherein each solution is a non-dominated solution; computing outranking weights for each pair of solutions; selecting a subset of the set of solutions based upon a defensive criteria in with respect to the outranking weights, wherein the defensive criteria relates to a number of solutions that outrank the subset; and outputting the subset of the set of solutions.