Genetic Algorithm with Punctuated Equilibria: Analysis of the Travelling Salesperson Problem Instance

1998 ◽  
Author(s):  
Daniel B. Ignat
Keyword(s):  
Genetic Algorithm ◽  
Problem Instance ◽  
Punctuated Equilibria ◽  
Travelling Salesperson Problem

scholarly journals Feature-Based Diversity Optimization for Problem Instance Classification

2020 ◽  
pp. 1-22
Author(s):  
Wanru Gao ◽  
Samadhi Nallaperuma ◽  
Frank Neumann
Keyword(s):  
Heuristic Search ◽  
General Framework ◽  
Problem Instance ◽  
Search Methods ◽  
Local Search Methods ◽  
Good Classification ◽  
Feature Based ◽  
Heuristic Search Methods ◽  
Travelling Salesperson Problem

Understanding the behaviour of heuristic search methods is a challenge. This even holds for simple local search methods such as 2-OPT for the Travelling Salesperson Problem (TSP). In this article, we present a general framework that is able to construct a diverse set of instances which are hard or easy for a given search heuristic. Such a diverse set is obtained by using an evolutionary algorithm for constructing hard or easy instances which are diverse with respect to different features of the underlying problem. Examining the constructed instance sets, we show that many combinations of two or three features give a good classification of the TSP instances in terms of whether they are hard to be solved by 2-OPT.

scholarly journals OPTIMASI RUTE PENGANTARAN PAKET MENGGUNAKAN METODE GENETIC ALGORITHM (GA)

2020 ◽  
Vol 10 (1) ◽  
pp. 41-44
Author(s):  
Hani Zulfia Zahro' ◽  
Febriana Santi Wahyuni
Keyword(s):  
Genetic Algorithm ◽  
Travelling Salesperson Problem

Meningkatnya jumlah pengguna smartphone pada saat ini, sejalan dengan jumlah pengakses toko online melalui web atau aplikasi.  Beberapa kemudahan yang ditawarkan oleh jenis pembelanjaan online menyebabkan perubahan perilaku konsumen dalam berbelanja, dari jenis pembelanjaan konvensional ke online.  Hal ini akan meningkatkan jumlah  pengantaran dari penyedia jasa pengantaran paket ke konsumen atau pembeli.  Permasalahan TSP (Travelling Salesperson Problem) adalah penentuan rute terbaik dari tempat asal ke tempat tujuan dan kembali ke tempat asal. Pada penentuan rute pengantaran suatu paket, tanpa harus mendatangi tempat yang sama lebih dari satu kali, jika hanya 10 tempat mudah untuk diselesaikan.  Namun jika lebih dari 30 tempat yang harus didatangi, maka ada banyak kemungkinan rute.  Beberapa teknik optimasi dapat digunakan untuk mengatasi masalah tersebut, diantaranya adalah Genetic Algorithm merupakan metode yang mengadaptasi teori evolusi Darwin yaitu genetika dan seleksi.  Proses dari metode Genetic Algorithm meliputi inisialisasi populasi awal, crossover, mutasi, perhitungan nilai Fitness, evaluasi, seleksi hingga di peroleh nilai populasi yang baru.  Dari implementasi optimasi menggunakan algoritma genetika diperoleh hasil rute dengan akumulasi jarak yang lebih pendek dibandingkan jika menggunakan metode optimasi yang lain.

A genetic algorithm for vehicle routing in logistic networks with practical constraints

2021 ◽  
Vol 68 (3) ◽  
pp. 16-40
Author(s):  
Grzegorz Koloch ◽  
Michał Lewandowski ◽  
Marcin Zientara ◽  
Grzegorz Grodecki ◽  
Piotr Matuszak ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Real Life ◽  
Capacity Constraints ◽  
Problem Instance ◽  
Postal Service ◽  
Genetic Operators ◽  
Delivery Problem ◽  
Network Time ◽  
Problem Instances ◽  
Practical Constraints

We optimise a postal delivery problem with time and capacity constraints imposed on vehicles and nodes of the logistic network. Time constraints relate to the duration of routes, whereas capacity constraints concern technical characteristics of vehicles and postal operation outlets. We consider a method which can be applied to a brownfield scenario, in which capacities of outlets can be relaxed and prospective hubs identified. As a solution, we apply a genetic algorithm and test its properties both in small case studies and in a simulated problem instance of a larger (i.e. comparable with real-world instances) size. We show that the genetic operators we employ are capable of switching between solutions based on direct origin-to-destination routes and solutions based on transfer connections, depending on what is more beneficial in a given problem instance. Moreover, the algorithm correctly identifies cases in which volumes should be shipped directly, and those in which it is optimal to use transfer connections within a single problem instance, if an instance in question requires such a selection for optimality. The algorithm is thus suitable for determining hubs and satellite locations. All considerations presented in this paper are motivated by real-life problem instances experienced by the Polish Post, the largest postal service provider in Poland, in its daily plans of delivering postal packages, letters and pallets.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
Sign in / Sign up

Export Citation Format

Share Document