fix general algo

js/matching-worker.js

@@ -176,7 +176,13 @@ class GeneticAlgorithm {
             const group = [];
             for (let j = 0; j < this.parallel; j++) {
                 const idx = indices[i * this.parallel + j];
-                group.push(this.cells[idx]);
+                // Safety check: ensure index is valid
+                if (idx >= 0 && idx < this.cells.length) {
+                    group.push(this.cells[idx]);
+                } else {
+                    // Fallback: use a random valid cell
+                    group.push(this.cells[Math.floor(Math.random() * this.cells.length)]);
+                }
             }
             configuration.push(group);
         }
@@ -184,31 +190,51 @@ class GeneticAlgorithm {
     }
 
     crossover(parent1, parent2) {
+        // Simple two-point crossover with repair
         const length = parent1.length;
-        const start = Math.floor(Math.random() * length);
-        const end = start + Math.floor(Math.random() * (length - start));
 
-        const child = new Array(length).fill(-1);
+        // 50% chance to just return a copy of one parent (with shuffle)
-        const usedIndices = new Set();
+        if (Math.random() < 0.5) {
-
+            const child = [...parent1];
-        for (let i = start; i <= end; i++) {
+            // Swap a few random positions
-            child[i] = parent1[i];
+            for (let i = 0; i < 2; i++) {
-            usedIndices.add(parent1[i]);
+                const a = Math.floor(Math.random() * length);
+                const b = Math.floor(Math.random() * length);
+                [child[a], child[b]] = [child[b], child[a]];
+            }
+            return child;
         }
 
-        let childIdx = (end + 1) % length;
+        // Otherwise, take half from each parent and repair duplicates
-        for (let i = 0; i < length; i++) {
+        const midpoint = Math.floor(length / 2);
-            const parent2Idx = (end + 1 + i) % length;
+        const child = [...parent1.slice(0, midpoint), ...parent2.slice(midpoint)];
-            if (!usedIndices.has(parent2[parent2Idx])) {
+
-                while (child[childIdx] !== -1) {
+        // Find and fix duplicates
-                    childIdx = (childIdx + 1) % length;
+        const seen = new Set();
-                }
+        const duplicatePositions = [];
-                child[childIdx] = parent2[parent2Idx];
+        const allIndices = new Set(parent1.concat(parent2));
-                usedIndices.add(parent2[parent2Idx]);
+
-                childIdx = (childIdx + 1) % length;
+        for (let i = 0; i < child.length; i++) {
+            if (seen.has(child[i])) {
+                duplicatePositions.push(i);
+            } else {
+                seen.add(child[i]);
             }
         }
 
+        // Find missing indices
+        const missing = [];
+        for (const idx of allIndices) {
+            if (!seen.has(idx)) {
+                missing.push(idx);
+            }
+        }
+
+        // Replace duplicates with missing values
+        for (let i = 0; i < duplicatePositions.length && i < missing.length; i++) {
+            child[duplicatePositions[i]] = missing[i];
+        }
+
         return child;
     }
 
@@ -276,6 +302,12 @@ class GeneticAlgorithm {
 
                 let child = this.crossover(parent1.indices, parent2.indices);
 
+                // Safety: ensure all indices are valid
+                child = child.map(idx => {
+                    if (idx >= 0 && idx < this.cells.length) return idx;
+                    return Math.floor(Math.random() * this.cells.length);
+                });
+
                 const usedLabels = new Set(child.map(idx => this.cells[idx].label));
                 const unusedCells = this.cells.filter(c => !usedLabels.has(c.label));