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COMP2051 Artificial Intelligence Methods
创建日期：2024-08-07 17:31:46
标签： COMP2051
Artificial Intelligence Methods

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Artificial Intelligence Methods (COMP2051 or AE2AIM)

Coursework: Perturbative hyper-heuristic for Bin Packing Problem

1. Introduction

Bin packing is one of the most studied combinatorial optimisation problems and has

applications in logistics, space planning, production, cloud computing, etc. Bin packing is

proven to be NP-Hard and the actual difficulties depend on both the size of the problem (i.e.

the total number of items to be packed) and other factors like the distribution of item sizes in

relation to the bin size as well as the number of distinct item sizes (different items may have a

same size).

In this coursework, you are asked to write a C/C++/Python program to solve this problem

using a perturbative hyper-heuristic method. In addition to submitting source code, a

written report (no more than 2000 words and 6 pages) is required to describe your algorithm

(see Section 4 for detailed requirements). Both your program and report must be completed

independently by yourself. The submitted documents must successfully pass a plagiarism

checker before they can be marked. Once a plagiarism case is established, the academic

misconduct policies shall be applied strictly.

This coursework carries 45% of the module marks.

2. Bin Packing Problem (BPP)

Given a set of n items, each item j has a size of aj, BPP aims to pack all items in the

minimum number of identical sized bins without violating the capacity of bins (V). The

problem can be mathematically formulated as follow:

Artificial Intelligence Methods (COMP2051 or AE2AIM) Coursework Ver1.0 2

This mathematical formulation is generally NOT solvable by existing integer programming

solvers like CPlex, Gurobi, LPSolve, especially when the number of items n is large. The

solution space of bin packing problem is characterised by its huge size and plateau-like that

makes it very challenging for traditional neighbourhood search methods. In order to

consistently solve the problem with good quality solutions, metaheuristics and hyperheuristics are used,

 which is the task of this coursework.

3. Problem instances

Over the years, a large number of BPP instances have been introduced by various research.

 In this coursework, we shall provide 3 instances files (binpack1.txt,

binpack3.txt and binpack11.txt), respectively representing easy, medium and hard instances.

From which 10 instances shall be selected for testing and evaluation of your algorithm in

marking. For each test instance, only 1 run is executed, and its objective value is used for

marking the performance component (see Section 5).

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