# Tag Info

Accepted

### What are the limitations of the hill climbing algorithm and how to overcome them?

As @nbro has already said that Hill Climbing is a family of local search algorithms. So, when you said Hill Climbing in the question I have assumed you are talking about the standard hill climbing. ...
• 2,023

### What are the limitations of the hill climbing algorithm and how to overcome them?

Hill climbing is not an algorithm, but a family of "local search" algorithms. Specific algorithms which fall into the category of "hill climbing" algorithms are 2-opt, 3-opt, 2.5-opt, 4-opt, or, in ...
• 41k

### Why is the larger value, as opposed to the smaller one, chosen, in the hill climbing algorithm?

When we climb a hill: We move higher in altitude. The person who is climbing, will always look for rocks/mud on the hill that are higher, so that he can climb higher. That is what the algorithm does ...
• 491

### When to choose Stochastic Hill Climbing over Steepest Hill Climbing?

Let's begin with some definitions first. Hill-climbing is a search algorithm simply runs a loop and continuously moves in the direction of increasing value-that is, uphill. The loop terminates when it ...
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### When to choose Stochastic Hill Climbing over Steepest Hill Climbing?

The steepest hill climbing algorithms works well for convex optimization. However, real world problems are typically of the non-convex optimization type: there are multiple peaks. In such cases, when ...
Accepted

### How is simulated annealing better than hill climbing methods?

In the least technical, most intuitive way possible: Simulated Annealing can be considered as a modification of Hill Climbing (or Hill Descent). Hill Climbing/Descent attempts to reach an optimum ...

### How can I formulate the map colouring problem as a hill climbing search problem?

First we have to specify the problem: Initial State: The map all colored randomly. Successor Function (Transition Model): Change the color of a region. Goal Test: The map all colored such that two ...
Accepted

### How can I formulate the map colouring problem as a hill climbing search problem?

First of all you need an initial solution. You will then improve this solution with hill climbing. For your initial solution, you can color the map randomly using the K colors. This will most likely ...
Accepted

### What is the difference between hill-climbing and greedy best-first search algorithms?

Let's see their definition first: Best First Search (BFS): ‌ Best-first search is a search algorithm that explores a graph by expanding the most promising node chosen according to a specified ...
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### Are there local search algorithms that make use of memory to give better solutions?

Tabu search uses memory to rule out parts of the neighborhood for local search, allowing the trajectory to typically pass through local optima instead of getting stuck in them.
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### Are there local search algorithms that make use of memory to give better solutions?

You could parallelize the search by dividing the global space in distinct regions/subsets. Then apply in each region a local search. This way you can search the global space systematically, more ...
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### Why does the hill climbing algorithm only produce a local maximum?

This part of your sentence is not always true "and not reached to final goal/solution". If you have just one maximum at all and it is finite, hill climbing (HL) can reach to it and it is a global ...
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### How do I solve the knapsack problem using the hill climbing algorithm?

I think there are at least three points that you need to think before implement Hill-Climbing (HC) algorithm: First, the initial state. In HC, people usually use a "temporary solution" for the ...
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### How does best-first search differ from hill-climbing?

Best-first search BFS is a search approach and not just a single algorithm, so there are many best-first (BFS) algorithms, such as greedy BFS, A* and B*. BFS algorithms are informed search algorithms, ...
• 41k
1 vote
Accepted

### Are hill climbing variations always optimal and complete?

No, they are prone to get stuck in local maxima, unless the whole search space is investigated. A simple algorithm will only ever move upwards; if you imagine you're in a mountain range, this will not ...
• 5,397
1 vote
Accepted

### How could we solve the TSP using a hill-climbing approach?

I will give you a basic idea of an approach. The basic idea behind hill climbing algorithms is to find local neighbouring solutions to the current one and, eventually, replace the current one with ...
• 41k
1 vote

### Should the mutation be applied with the hill climbing algorithm?

In general, hill climbing algorithms select a random initial solution, then takes the best move available after evaluating all possible operations available. The possible operations are determined by ...
• 823
1 vote

### Why is the larger value, as opposed to the smaller one, chosen, in the hill climbing algorithm?

There is no reason why you can't have a hill descending algorithm, instead of finding maxima you will find minima. If that is what your aim is, it's still called a hill climbing algorithm, I guess...
• 324
1 vote

### When to choose Stochastic Hill Climbing over Steepest Hill Climbing?

I'm new to these concepts too, but the way I've understood it, Stochastic hill climbing would perform better in cases where computation time is precious (includes the calculation of the fitness ...
• 491

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