Add tutorial READMEs and fix tutorial return codes

Add README.md files for moeo/tutorial/Lesson{1-4}, smp/tutorial/Lesson{1-4},
and mo/tutorial/Lesson9 — these tutorials had no documentation.

Fix return 1 → return 0 in 28 tutorial main() functions across mo/ and
smp/ that unconditionally returned failure status.

moeo/tutorial/Lesson1/README.md

@@ -0,0 +1,84 @@
+# How to run your first multi-objective EA?
+
+In this lesson you will solve the Schaffer SCH1 bi-objective problem with
+NSGA-II using the ParadisEO-MOEO framework.
+
+The SCH1 problem minimizes two objectives over a single real-valued
+variable x in [0, 2]:
+
+- f1(x) = x^2
+- f2(x) = (x - 2)^2
+
+## 1. Running
+
+From the `build/moeo/tutorial/Lesson1` directory:
+
+```shell
+./Sch1 --help
+./Sch1 --popSize=100 --maxGen=100
+```
+
+Parameters can also be read from a file:
+
+```shell
+./Sch1 @Sch1.param
+```
+
+## 2. Browsing the code
+
+Open `Sch1.cpp` and follow along.
+
+First, define the objective vector traits. This tells MOEO how many
+objectives the problem has and whether each is minimizing or maximizing:
+
+```c++
+class Sch1ObjectiveVectorTraits : public moeoObjectiveVectorTraits
+{
+public:
+    static bool minimizing (int) { return true; }
+    static bool maximizing (int) { return false; }
+    static unsigned int nObjectives () { return 2; }
+};
+```
+
+The solution class `Sch1` inherits from `moeoRealVector` — a real-valued
+decision vector that also carries an objective vector:
+
+```c++
+class Sch1 : public moeoRealVector < Sch1ObjectiveVector >
+{
+public:
+    Sch1() : moeoRealVector < Sch1ObjectiveVector > (1) {}
+};
+```
+
+The evaluator computes both objectives and stores them via
+`objectiveVector()`:
+
+```c++
+void operator () (Sch1 & _sch1)
+{
+    if (_sch1.invalidObjectiveVector()) {
+        Sch1ObjectiveVector objVec;
+        double x = _sch1[0];
+        objVec[0] = x * x;
+        objVec[1] = (x - 2.0) * (x - 2.0);
+        _sch1.objectiveVector(objVec);
+    }
+}
+```
+
+The algorithm itself is a single line — `moeoNSGAII` takes the generation
+limit, evaluator, crossover, and mutation as constructor arguments:
+
+```c++
+moeoNSGAII < Sch1 > nsgaII (MAX_GEN, eval, xover, P_CROSS, mutation, P_MUT);
+```
+
+After the run, extract the Pareto front with `moeoUnboundedArchive`:
+
+```c++
+moeoUnboundedArchive < Sch1 > arch;
+arch(pop);
+arch.sortedPrintOn(cout);
+```