diff --git a/tig-algorithms/src/vehicle_routing/mod.rs b/tig-algorithms/src/vehicle_routing/mod.rs
index 930b4fb..42ddab4 100644
--- a/tig-algorithms/src/vehicle_routing/mod.rs
+++ b/tig-algorithms/src/vehicle_routing/mod.rs
@@ -126,7 +126,8 @@
 
 // c002_a064
 
-// c002_a065
+pub mod new_enhanced_cw_low;
+pub use new_enhanced_cw_low as c002_a065;
 
 // c002_a066
 
diff --git a/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/README.md b/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/README.md
new file mode 100644
index 0000000..9f92804
--- /dev/null
+++ b/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/README.md
@@ -0,0 +1,23 @@
+# TIG Code Submission
+
+    ## Submission Details
+
+    * **Challenge Name:** vehicle_routing
+    * **Submission Name:** new_enhanced_cw_low
+    * **Copyright:** 2025 syebastian
+    * **Identity of Submitter:** syebastian
+    * **Identity of Creator of Algorithmic Method:** null
+    * **Unique Algorithm Identifier (UAI):** null
+
+    ## License
+
+    The files in this folder are under the following licenses:
+    * TIG Benchmarker Outbound License
+    * TIG Commercial License
+    * TIG Inbound Game License
+    * TIG Innovator Outbound Game License
+    * TIG Open Data License
+    * TIG THV Game License
+
+    Copies of the licenses can be obtained at:  
+    https://github.com/tig-foundation/tig-monorepo/tree/main/docs/licenses
\ No newline at end of file
diff --git a/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/mod.rs b/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/mod.rs
new file mode 100644
index 0000000..01627c6
--- /dev/null
+++ b/tig-algorithms/src/vehicle_routing/new_enhanced_cw_low/mod.rs
@@ -0,0 +1,644 @@
+use anyhow::{anyhow, Result};
+use serde_json::{Map, Value};
+use tig_challenges::vehicle_routing::*;
+
+
+pub fn solve_challenge(
+    challenge: &Challenge,
+    save_solution: &dyn Fn(&Solution) -> Result<()>,
+    hyperparameters: &Option<Map<String, Value>>,
+) -> Result<()> {
+    Err(anyhow!("This algorithm is no longer compatible."))
+}
+
+// Old code that is no longer compatible
+#[cfg(none)]
+mod dead_code {
+    use rand::{rngs::{SmallRng, StdRng}, Rng, SeedableRng};
+    use tig_challenges::vehicle_routing::*;
+
+
+    pub fn solve_challenge(challenge: &Challenge) -> anyhow::Result<Option<Solution>> {
+        let mut solution = Solution {
+            sub_solutions: Vec::new(),
+        };
+        for sub_instance in &challenge.sub_instances {
+            match solve_sub_instance(sub_instance)? {
+                Some(sub_solution) => solution.sub_solutions.push(sub_solution),
+                None => return Ok(None),
+            }
+        }
+        Ok(Some(solution))
+    }
+
+    pub fn solve_sub_instance(challenge: &SubInstance) -> anyhow::Result<Option<SubSolution>> {
+        let mut global_best_solution: Option<SubSolution> = None;
+        let mut global_best_cost = std::i32::MAX;
+    
+        const OUTER_ITERATIONS: usize = 1;
+        let iterations_per_outer = [5000, 10000, 10000];
+        let inner_iters_per_outer = [4, 1, 1];
+        let num_nodes = challenge.difficulty.num_nodes;
+
+        let mut rng = SmallRng::seed_from_u64(u64::from_le_bytes(challenge.seed[..8].try_into().unwrap()));
+
+        let max_dist: f32 = challenge.distance_matrix[0].iter().sum::<i32>() as f32;
+        let p = challenge.baseline_total_distance as f32 / max_dist;
+        if p < 0.55 {
+            return Ok(None)
+        }
+
+        let mut promising = false;
+        let mut iteration_results: Vec<(Vec<u32>, i32)> = Vec::new();
+
+        let mut best_outer_params : Vec<u32> = Vec::new();
+
+        for outer_iter in 0..OUTER_ITERATIONS {
+            let num_iterations = iterations_per_outer[outer_iter];
+            let inner_iterations = inner_iters_per_outer[outer_iter];
+
+            for inner_iter in 0..inner_iterations {
+                let mut savings = Savings::new(challenge);
+                savings.sort_stable();
+
+                let mut current_params = vec![25; num_nodes];
+
+                let mut current_solution = create_solution(challenge, &savings.stable_list);
+                let mut current_cost = calculate_solution_cost(&current_solution, &challenge.distance_matrix);
+            
+                if current_cost <= challenge.baseline_total_distance {
+                    return Ok(Some(current_solution));
+                }
+    
+                if (current_cost as f32 * 0.95) > challenge.baseline_total_distance as f32 && !promising {
+                    return Ok(None);
+                }
+                else {
+                    promising = true;
+                }    
+
+                savings.build_supplementary_structs(challenge);
+
+                let mut best_solution = Some(SubSolution { routes: current_solution.routes.clone() });
+                let mut best_cost = current_cost;
+            
+                for i in 0..num_iterations {
+                    let (mut neighbor_params, mut modified_indices) = generate_neighbor(
+                        &current_params, 
+                        best_solution.as_ref().unwrap(),
+                        &challenge,
+                        &mut rng, 
+                        i, 
+                        num_iterations
+                    );
+                
+                    if outer_iter > 0 && i == 0 {
+                        neighbor_params = best_outer_params.clone();
+                        modified_indices = (0..num_nodes).collect();
+                    };
+
+                    if !savings.recompute_savings(&neighbor_params, &modified_indices) {
+                        continue;
+                    }
+
+                    let mut neighbor_solution = create_solution(challenge, &savings.unstable_list);
+                    postprocess_solution(
+                        &mut neighbor_solution,
+                        &challenge.distance_matrix,
+                        &challenge.demands,
+                        challenge.max_capacity,
+                    );
+
+                    let neighbor_cost = calculate_solution_cost(&neighbor_solution, &challenge.distance_matrix);
+
+                    let delta = neighbor_cost - current_cost;
+                    if delta <= 0 {
+                        current_params = neighbor_params;
+                        current_cost = neighbor_cost;
+                        current_solution = neighbor_solution;
+                        savings.apply_unstable_list();
+                    
+                        if current_cost < best_cost {
+                            best_cost = current_cost;
+                            best_solution = Some(SubSolution {
+                                routes: current_solution.routes.clone(),
+                            });
+                        }
+                        if best_cost <= challenge.baseline_total_distance {
+                            return Ok(best_solution);
+                        }
+                    }
+                }
+
+                iteration_results.push((
+                    current_params,
+                    best_cost
+                ));
+
+                if best_cost < global_best_cost {
+                    global_best_cost = best_cost;
+                    global_best_solution = best_solution;
+                }
+            }
+
+            if outer_iter < OUTER_ITERATIONS - 1 {
+                let (best_params, best_cost) = iteration_results.iter()
+                    .min_by_key(|&(_, cost)| cost)
+                    .map(|(params, cost)| (params.clone(), *cost))
+                    .unwrap();
+
+                iteration_results.clear();
+                best_outer_params = best_params;
+            }
+        }
+
+        Ok(global_best_solution)
+    }
+
+    pub struct Savings {
+        pub stable_list: Vec<(u32, u16, u16)>,
+
+        raw_savings: Vec<Vec<u32>>,
+        pub pair_map: Vec<Vec<u64>>,
+        pub unstable_list: Vec<(u32, u16, u16)>,
+    }
+
+    impl Savings {
+        pub fn new(challenge: &SubInstance) -> Self {
+            let stable_list = Self::create_initial_savings_list(challenge);
+
+            Self {
+                stable_list,
+                raw_savings: Vec::new(),
+                pair_map: Vec::new(),
+                unstable_list: Vec::new(),
+            }
+        }
+
+        fn create_initial_savings_list(challenge: &SubInstance) -> Vec<(u32, u16, u16)> {
+            let num_nodes = challenge.difficulty.num_nodes;
+
+            let max_distance = challenge
+                .distance_matrix
+                .iter()
+                .flat_map(|row| row.iter())
+                .cloned()
+                .max()
+                .unwrap_or(0);
+            let threshold = max_distance / 3;
+        
+            let capacity = ((num_nodes - 1) * (num_nodes - 2)) / 2;
+            let mut savings = Vec::with_capacity(capacity);
+
+            for i in 1..num_nodes {
+                for j in (i + 1)..num_nodes {
+                    let dist_ij = challenge.distance_matrix[i][j];
+                    if dist_ij <= threshold {
+                        let saving = challenge.distance_matrix[0][i] + challenge.distance_matrix[j][0] - dist_ij;
+                        if saving > 0 {
+                            savings.push((!(saving as u32), i as u16, j as u16));
+                        }
+                    }
+                }
+            }
+            savings
+        }
+
+        pub fn build_supplementary_structs(&mut self, challenge: &SubInstance) {
+            let num_nodes = challenge.difficulty.num_nodes;
+            let mask_size = (num_nodes + 63) / 64;  // Calculate number of u64 chunks needed
+    
+            // Initialize pair_map as a bitmask with 64-bit chunks
+            self.pair_map = vec![vec![0u64; mask_size]; num_nodes];
+            self.raw_savings = vec![vec![0; num_nodes]; num_nodes];
+        
+            for &(_, i16, j16) in &self.stable_list {
+                let (i, j) = (i16 as usize, j16 as usize);
+                let saving = challenge.distance_matrix[0][i]
+                    + challenge.distance_matrix[j][0]
+                    - challenge.distance_matrix[i][j];
+    
+                self.raw_savings[i][j] = saving as u32;
+                self.raw_savings[j][i] = saving as u32;
+    
+                let (idx, bit) = (j / 64, j % 64);
+                self.pair_map[i][idx] |= 1u64 << bit;
+    
+                let (idx, bit) = (i / 64, i % 64);
+                self.pair_map[j][idx] |= 1u64 << bit;
+            }
+    
+            self.unstable_list = Vec::with_capacity(self.stable_list.len());
+            self.unstable_list.resize(self.stable_list.len(), (0, 0, 0));
+        }
+
+        fn radix_sort(savings_list: &mut [(u32, u16, u16)]) {
+            unsafe {
+                // 1. Use usize for counts to prevent overflow with large arrays
+                let mut counts_low = [0u32; 512];
+                let mut counts_high = [0u32; 512];
+                let mut buf = Vec::with_capacity(savings_list.len());
+                buf.set_len(savings_list.len());
+            
+                let savings_ptr : *mut (u32, u16, u16) = savings_list.as_mut_ptr();
+                let buf_ptr : *mut (u32, u16, u16) = buf.as_mut_ptr();
+
+                let mut ptr = savings_ptr;
+                for _ in 0..savings_list.len() {
+                    let bits = (*ptr).0;
+                    counts_low[(bits & 511) as usize] += 1;
+                    counts_high[((bits >> 9) & 511) as usize] += 1;
+                    ptr = ptr.add(1);
+                }
+
+                let mut total_low = 0;
+                let mut total_high = 0;
+                for i in 0..512 {
+                    let cl = counts_low[i];
+                    let ch = counts_high[i];
+                    counts_low[i] = total_low;
+                    counts_high[i] = total_high;
+                    total_low += cl;
+                    total_high += ch;
+                }
+
+                let mut src = savings_ptr;
+                let mut dst = buf_ptr;
+                for _ in 0..savings_list.len() {
+                    let item = *src;
+                    let byte = (item.0 & 511) as usize;
+                    let pos = counts_low[byte] as usize;
+                    *dst.add(pos) = item;
+                    counts_low[byte] += 1;
+                    src = src.add(1);
+                }
+
+                let mut src = buf_ptr;
+                let mut dst = savings_ptr;
+                for _ in 0..savings_list.len() {
+                    let item = *src;
+                    let byte = ((item.0 >> 9) & 511) as usize;
+                    let pos = counts_high[byte] as usize;
+                    *dst.add(pos) = item;
+                    counts_high[byte] += 1;
+                    src = src.add(1);
+                }
+            }
+        }
+
+        pub fn recompute_savings(&mut self, params: &[u32], modified_indices: &[usize]) -> bool {
+            let num_nodes = params.len();
+            let mut reduced_savings = Vec::with_capacity(modified_indices.len() * num_nodes / 10);
+            let mut modified = vec![false; num_nodes];
+        
+            let mut mask_len = (num_nodes + 63) / 64;
+            let mut visited = vec![0u64; mask_len];
+
+            unsafe {
+                for &i in modified_indices {
+                    for k in 0..mask_len {
+                        let chunk = *self.pair_map.get_unchecked(i).get_unchecked(k);
+                        let mut unvisited_pairs_mask = chunk & !visited[k];
+                    
+                        while unvisited_pairs_mask != 0 {
+                            let bit_pos = unvisited_pairs_mask.trailing_zeros() as usize;
+                            let j = bit_pos + 64 * k;
+
+                            let base_saving = *self.raw_savings.get_unchecked(i).get_unchecked(j);
+                            let new_score = (*params.get_unchecked(i) + *params.get_unchecked(j)) * base_saving;
+                            reduced_savings.push((!new_score, i as u16, j as u16));
+    
+                            unvisited_pairs_mask &= unvisited_pairs_mask - 1;
+                        }
+                    }
+                    let (idx, bit) = (i / 64, i % 64);
+                    *visited.get_unchecked_mut(idx) |= 1 << bit;
+                    modified[i] = true;
+                }
+            }
+ 
+            if reduced_savings.len() == 0 {
+                return false;
+            }
+            Self::radix_sort(&mut reduced_savings);
+
+            let mut stable_idx = 0;
+            let mut reduced_idx = 0;
+            let mut k = 0;
+    
+            while stable_idx < self.stable_list.len() 
+                && (modified[self.stable_list[stable_idx].1 as usize] 
+                 || modified[self.stable_list[stable_idx].2 as usize]) {
+                stable_idx += 1;
+            }
+
+            while stable_idx < self.stable_list.len() && reduced_idx < reduced_savings.len() {
+                let stable_entry = self.stable_list[stable_idx];
+                let reduced_entry = reduced_savings[reduced_idx];
+    
+                if stable_entry.0 < reduced_entry.0 {
+                    self.unstable_list[k] = stable_entry;
+                
+                    stable_idx += 1;
+                    while stable_idx < self.stable_list.len() 
+                        && (modified[self.stable_list[stable_idx].1 as usize] 
+                         || modified[self.stable_list[stable_idx].2 as usize]) {
+                        stable_idx += 1;
+                    }
+                } else {
+                    self.unstable_list[k] = reduced_entry;
+                    reduced_idx += 1;
+                }
+                k += 1;
+            }
+    
+            while stable_idx < self.stable_list.len() {
+                let entry = self.stable_list[stable_idx];
+
+                if !modified[entry.1 as usize] && !modified[entry.2 as usize] {
+                    self.unstable_list[k] = entry;
+                    k += 1;
+                }
+                stable_idx += 1;
+            }
+    
+            while reduced_idx < reduced_savings.len() {
+                self.unstable_list[k] = reduced_savings[reduced_idx];
+                k += 1;
+                reduced_idx += 1;
+            }
+            return true;
+        }
+
+        pub fn apply_unstable_list(&mut self) {
+            std::mem::swap(&mut self.stable_list, &mut self.unstable_list);
+        }
+    
+        pub fn sort_stable(&mut self) {
+            Self::radix_sort(&mut self.stable_list);
+        }
+    }
+
+    fn generate_neighbor<R: Rng + ?Sized>(
+        current: &[u32],
+        best_solution: &SubSolution,
+        challenge : &SubInstance,
+        rng: &mut R,
+        iteration: usize,
+        max_iterations: usize,
+    ) -> (Vec<u32>, Vec<usize>) {
+        let progress = iteration as f32 / max_iterations as f32;
+        let base_prob = 0.5 * (-5.0 * progress).exp() + 0.04;
+        let max_steps = 2;
+
+        let mut result = current.to_vec();
+        let mut modified_indices = Vec::with_capacity(challenge.difficulty.num_nodes / 2);
+    
+        while modified_indices.is_empty() {
+            for (i, &param) in current.iter().enumerate() {
+                if rng.gen_bool(base_prob as f64) {
+                    let steps = rng.gen_range(1..=max_steps);
+                
+                    let sign = if rng.gen_bool(0.5) { 1 } else { -1 };
+                    result[i] = (param as i32 + sign * steps).clamp(25, 50) as u32;
+                    modified_indices.push(i);
+                }
+            }
+        }
+
+        let mut pairs = Vec::with_capacity(3 * challenge.difficulty.num_nodes);
+        for route in &best_solution.routes {
+            for i in 1..route.len()-1 {
+                for j in i+1..route.len()-1 {
+                    pairs.push((route[i], route[j]));
+                }
+            }
+        }
+
+        if pairs.len() > 0{
+            let pair_idx = rng.gen_range(0..pairs.len());
+            let idx1 = pairs[pair_idx].0;
+            let idx2 = pairs[pair_idx].1;
+        
+            result.swap(idx1, idx2);
+        
+            if !modified_indices.contains(&idx1) {
+                modified_indices.push(idx1);
+            }
+            if !modified_indices.contains(&idx2) {
+                modified_indices.push(idx2);
+            }
+        }
+    
+        (result, modified_indices)
+    }
+
+    #[inline]
+    fn calculate_solution_cost(solution: &SubSolution, distance_matrix: &Vec<Vec<i32>>) -> i32 {
+        solution
+            .routes
+            .iter()
+            .map(|route| {
+                route.windows(2).map(|pair| distance_matrix[pair[0]][pair[1]]).sum::<i32>()
+            })
+            .sum()
+    }
+
+    #[inline(never)]
+    fn create_solution(
+        challenge: &SubInstance,
+        savings_list: &[(u32, u16, u16)]
+    ) -> SubSolution {
+        let num_nodes = challenge.difficulty.num_nodes;
+        let demands = &challenge.demands;
+        let max_capacity = challenge.max_capacity;
+
+        let mut node_links: Vec<[Option<usize>; 2]> = vec![[None, None]; num_nodes];
+        let mut route : Vec<(usize, usize)>  = (0..num_nodes)
+            .map(|i| (i, i))
+            .collect();
+
+        let mut route_demands = demands.clone();
+
+        for &(_, i16, j16) in savings_list {
+            let (i, j) = (i16 as usize, j16 as usize);
+        
+            let route_demands_left = route_demands[i];
+            let route_demands_right = route_demands[j];
+            if route_demands_left + route_demands_right > max_capacity {
+                continue;
+            }
+
+            let route_i_start = route[i].0;
+            let route_j_start = route[j].0;
+            let route_i_end = route[i].1;
+            let route_j_end = route[j].1;
+            if route_i_start == route_j_start || route_i_start == route_j_end 
+                || route_i_end == route_j_start || route_i_end == route_j_end {
+                continue;
+            }
+
+            let node_i_left = node_links[i][0];
+            let node_i_right = node_links[i][1];
+
+            let node_j_left = node_links[j][0];
+            let node_j_right = node_links[j][1];
+
+            let mut dir_i = usize::from(node_i_left.is_some());
+            let mut dir_j = usize::from(node_j_left.is_some());
+
+            node_links[i][dir_i] = Some(j);
+            node_links[j][dir_j] = Some(i);
+        
+            if node_i_left.is_some() || node_i_right.is_some() {
+                route_demands[i] = max_capacity + 1;
+            }
+            if node_j_left.is_some() || node_j_right.is_some() {
+                route_demands[j] = max_capacity + 1;
+            }
+
+            let opposite_i = if route_i_start == i {
+                route_i_end
+            } else {
+                route_i_start
+            };
+
+            let opposite_j = if route_j_start == j {
+                route_j_end
+            } else {
+                route_j_start
+            };
+
+            let new_route = (opposite_i, opposite_j);
+            route[opposite_i] = new_route;
+            route[opposite_j] = new_route;
+
+            let combined_demand = route_demands_left + route_demands_right;
+            route_demands[opposite_i] = combined_demand;
+            route_demands[opposite_j] = combined_demand;
+        }
+
+        let final_routes = extract_routes(
+            num_nodes,
+            &route_demands,
+            max_capacity,
+            &route,
+            &node_links
+        );
+    
+        SubSolution { routes: final_routes }
+    }
+
+    #[inline(never)]
+    fn extract_routes(
+        num_nodes: usize,
+        route_demands: &[i32],
+        max_capacity: i32,
+        route: &[(usize, usize)],
+        node_links: &[[Option<usize>; 2]],
+    ) -> Vec<Vec<usize>> {
+        let mut visited = vec![false; num_nodes];
+    
+        let mut all_nodes = Vec::with_capacity(3 * num_nodes);
+        let mut final_routes = Vec::with_capacity(num_nodes / 2);
+    
+        for i in 1..num_nodes {
+            if route_demands[i] > max_capacity || route[i].0 != i {
+                continue;   
+            }
+            let route_start_idx = all_nodes.len();
+        
+            let mut route_iter = i;
+            let route_end = route[i].1;
+
+            all_nodes.push(0);
+            all_nodes.push(route_iter);
+            visited[route_iter] = true;
+        
+            while route_iter != route_end {
+                let links = node_links[route_iter];
+                let next = match links {
+                    [Some(left), Some(right)] => {
+                        if !visited[left] { left } else { right }
+                    },
+                    [Some(next), None] | [None, Some(next)] => next,
+                    _ => break,
+                };
+                route_iter = next;
+                all_nodes.push(route_iter);
+                visited[route_iter] = true;
+            }
+            all_nodes.push(0);
+
+            let route_len = all_nodes.len() - route_start_idx;
+            final_routes.push(all_nodes[route_start_idx..all_nodes.len()].to_vec());
+        }
+    
+        final_routes
+    }
+
+
+    #[inline(never)]
+    pub fn postprocess_solution(
+        solution: &mut SubSolution,
+        distance_matrix: &Vec<Vec<i32>>,
+        _demands: &Vec<i32>,
+        _max_capacity: i32, 
+    ) {
+        for route in solution.routes.iter_mut() {
+            unsafe { two_opt_best_unsafe(route, distance_matrix) };
+        }
+    }
+
+    #[inline]
+    unsafe fn two_opt_best_unsafe(route: &mut Vec<usize>, distance_matrix: &Vec<Vec<i32>>) -> bool {
+        let n = route.len();
+        if n < 4 {
+            return false;
+        }
+
+        let mut any_improvement = false;
+        let route_slice = route.as_mut_slice();
+
+        loop {
+            let mut improved = false;
+        
+            for i in 1..(n - 2) {
+                let mut best_gain = 0;
+                let mut best_j = 0;
+            
+                let i_range = i..(n - 1);
+                for j in i_range.skip(1) {
+                    let ri_m1 = *route_slice.get_unchecked(i - 1);
+                    let ri = *route_slice.get_unchecked(i);
+                    let rj = *route_slice.get_unchecked(j);
+                    let rj_p1 = *route_slice.get_unchecked(j + 1);
+
+                    let current = distance_matrix.get_unchecked(ri_m1).get_unchecked(ri);
+                    let candidate = distance_matrix.get_unchecked(rj).get_unchecked(rj_p1);
+                    let new_connection = distance_matrix.get_unchecked(ri_m1).get_unchecked(rj);
+                    let broken_connection = distance_matrix.get_unchecked(ri).get_unchecked(rj_p1);
+
+                    let gain = current + candidate - new_connection - broken_connection;
+
+                    if gain > best_gain {
+                        best_gain = gain;
+                        best_j = j;
+                    }
+                }
+            
+                if best_gain > 0 {
+                    route_slice[i..=best_j].reverse();
+                    improved = true;
+                    any_improvement = true;
+                }
+            }
+        
+            if !improved {
+                break;
+            }
+        }
+    
+        any_improvement
+    }
+}
\ No newline at end of file