如何创建自动车辆路线模拟？

Question

I want to create a vehicle routing optimization program. I will have multiple vehicles travelling and delivering items by finding the shortest path from A to B. At first I will simply output results. I may later create a visual representation of the program.

It has been suggested to me that I will find it easiest to do this in Python.

I have to do this task, but it seems very daunting. I am not the best programmer yet, but not a beginner either, I am good at maths and a quick learner.

Any advice on how to break down this task would be really helpful. Should I use Python? Any Python modules that will be particularly suited to this task?

Answer 1

Psuedo code for A* algorithm from http://en.wikipedia.org/wiki/A*_search_algorithm

function A*(start,goal)
closedset := the empty set    // The set of nodes already evaluated.
openset := {start}    // The set of tentative nodes to be evaluated, initially containing the start node
came_from := the empty map    // The map of navigated nodes.

g_score[start] := 0    // Cost from start along best known path.
// Estimated total cost from start to goal through y.
f_score[start] := g_score[start] + heuristic_cost_estimate(start, goal)

while openset is not empty
    current := the node in openset having the lowest f_score[] value
    if current = goal
        return reconstruct_path(came_from, goal)

    remove current from openset
    add current to closedset
    for each neighbor in neighbor_nodes(current)
        if neighbor in closedset
            continue
        tentative_g_score := g_score[current] + dist_between(current,neighbor)

        if neighbor not in openset or tentative_g_score < g_score[neighbor] 
            came_from[neighbor] := current
            g_score[neighbor] := tentative_g_score
            f_score[neighbor] := g_score[neighbor] + heuristic_cost_estimate(neighbor, goal)
            if neighbor not in openset
                add neighbor to openset

return failure

function reconstruct_path(came_from,current)
    total_path := [current]
    while current in came_from:
        current := came_from[current]
        total_path.append(current)
    return total_path

This is the most common and pratical way to find the shortest path. It basically scans the surrounding area until the start point and check point are met and it stops at any barriers

And depending on how hefty your program is python is not the best because of its slower execution speeds compared with other languages. If your looking for simplicity python is your best friend.

Answer 2

I used networkx the other day, and it was superb. Very easy to use, and very quick.

So you'll need to get your data into some kind of usable format, and then run your algorithms through this.

Python is often a good choice for scripting and pulling together pieces of data and analysing them!