I create this code and it seems not to have any error however the results are NULL , is there any;thing else I have to do .

[MALVIS]

f.mean <- mean
library("MASS")
library("Matrix")
library("igraph")
library("data.table")

Truck <- function(name, capacity, speed, route, trash_collected = 0) {
  list(name = name, capacity = capacity, speed = speed, route = route, trash_collected = trash_collected)
}

Block <- function(name, trash_per_day) {
  list(name = name, trash_per_day = trash_per_day)
}

DaysOfTheWeek <- setNames(1:7, c("monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"))

TruckRouting <- function(num_blocks, mean = 7, sigma = 2) {
  adj_matrix <- create_map(num_blocks, mean, sigma)
  list(num_blocks = num_blocks, mean = mean, sigma = sigma, adj_matrix = adj_matrix)
}
create_map <- function(num_blocks, mean, sigma) {
  new_map <- matrix(0, nrow = num_blocks, ncol = num_blocks)
  for (i in seq(1,num_blocks)) {
    for (j in seq(1,num_blocks)) {
      if (i == j) {
        new_map[i, j] <- Inf
      } else {
        new_map[i, j] <- as.integer(log(rlnorm(1, mean, sigma)))
      }
    }
  }
  return (new_map)
}

generate_truck_route <- function(adj_matrix, start_block, end_block) {
  unvisited_blocks <- setdiff(seq_along(adj_matrix), start_block)
  truck_route <- c(start_block)
  while (length(unvisited_blocks) > 0 && truck_route[length(truck_route)] != end_block) {
    next_block <- unvisited_blocks[which.min(adj_matrix[truck_route[length(truck_route)], unvisited_blocks])]
    
    truck_route <- c(truck_route, next_block)
    unvisited_blocks <- setdiff(unvisited_blocks, next_block)
  }
  return (truck_route)
}


create_trucks <- function(num_trucks, truck_routing) {
  end_blocks <- c(10, 20)
  truck_routes <- lapply(end_blocks, function(end_block) generate_truck_route(truck_routing$adj_matrix, 1, end_block))
  return (lapply(seq_len(num_trucks), function(i) Truck(paste0("truck ", i), 500, 30, truck_routes[[i]])))
}

collect_trash <- function(truck, block, time_available) {
  if (truck$capacity >= block$trash & time_available >= block$distance) {
    truck$trash_collected <- truck$trash_collected + block$trash
    truck$capacity <- truck$capacity - block$trash
    block$trash <- 0
  } else if (truck$capacity >= block$trash) {
    truck$trash_collected <- truck$trash_collected + (block$trash * (time_available / block$distance))
    truck$capacity <- truck$capacity - (block$trash * (time_available / block$distance))
    block$trash <- 0
  } else if (time_available >= block$distance) {
    truck$trash_collected <- truck$trash_collected + truck$capacity
    block$trash <- block$trash - truck$capacity
    truck$capacity <- 0
  } else {
    truck$trash_collected <- truck$trash_collected + (truck$capacity * (time_available / block$distance))
    block$trash <- block$trash - (truck$capacity * (time_available / block$distance))
    truck$capacity <- 0
  }
}

run_shift <- function(truck, blocks, landfill_distance, shift_hours) {
  time_per_block <- shift_hours / length(blocks)
  for (block in blocks) {
    time_available <- time_per_block - (block$distance / truck$speed)
    collect_trash(truck, block, time_available)
  }
  wait_at_landfill(truck, landfill_distance)
}

wait_at_landfill <- function(truck, landfill_distance) {
  time_waiting <- landfill_distance / truck$speed
  # Wait at landfill until the next shift starts
}



create_blocks <- function(num_blocks, total_trash_per_day) {
  trash_per_block <- total_trash_per_day / num_blocks
  blocks <- lapply(1:num_blocks, function(i) {
    Block <- list(name = paste0("block ", i), distance = sample(1:10, 1), trash_per_day = trash_per_block)
    return(Block)
  })
  return(blocks)
}

simulate_trucks <- function(trucks, blocks, special_increments=NULL) {
  trash_left <- sapply(blocks, function(block) block$trash_per_day)
  trash_collected <- rep(0, length(trucks))
  trash_left_per_shift <- data.frame(block_index = integer(), trash_left = numeric())
  
  for (truck_idx in seq_along(trucks)) {
    truck <- trucks[[truck_idx]]
    for (block_idx in seq_along(blocks)) {
      if (!(block_idx %in% truck$route)) {
        next
      }
      time_to_block <- sum(sapply(1:(length(truck$route)-1), function(i) {
        if (truck$route[i+1] != block_idx) {
          truck$adj_matrix[truck$route[i], truck$route[i+1]] / truck$speed
        } else {
          0
        }
      }))
      time_available <- 8 - time_to_block  # Assuming an 8 hour shift for now
      if (!is.null(special_increments) && block_idx %in% names(special_increments)) {
        time_available <- time_available + special_increments[[as.character(block_idx)]]
      }
      truck$collect_trash(blocks[[block_idx]], time_available)
      trash_left[block_idx] <- trash_left[block_idx] - truck$trash_collected
      trash_collected[truck_idx] <- trash_collected[truck_idx] + truck$trash_collected
      truck$trash_collected <- 0
    }
    landfill_distance <- sum(sapply(1:(length(truck$route)-1), function(i) truck$adj_matrix[truck$route[i], truck$route[i+1]]))
    truck$wait_at_landfill(landfill_distance)
  }
  
  for (block_idx in seq_along(blocks)) {
    shift <- (block_idx %% length(trash_left_per_shift)) + 1
    trash_left_per_shift <- rbind(trash_left_per_shift, data.frame(block_index = block_idx, trash_left = trash_left[block_idx], shift = shift))
  }
  
  return(list(trash_collected = trash_collected, trash_left_per_shift = trash_left_per_shift))
}

calculate_total_trash_collected <- function(trucks, blocks, special_increments=NULL) {
  results <- simulate_trucks(trucks, blocks, special_increments)
  return(sum(results$trash_collected))
}

write_trash_left_to_csv <- function(trucks, blocks, special_increments=NULL, filename='trash_left.csv') {
  results <- simulate_trucks(trucks, blocks, special_increments)
  write.csv(results$trash_left_per_shift, filename, row.names = FALSE)
  
}

I am not sure if I need to used [i] to save the information or if the code is wrong ,

[nirgrahamuk]

did you simply forget to call the functions that you wrote ?