Applying Ant Colony Optimization to the Capacitated Arc Routing Problem

2004 ◽  
pp. 420-421 ◽  
Author(s):  
Karl F. Doerner ◽  
Richard F. Hartl ◽  
Vittorio Maniezzo ◽  
Marc Reimann
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Arc Routing ◽  
Routing Problem ◽  
Capacitated Arc Routing Problem ◽  
Capacitated Arc Routing

scholarly journals A New Ant Colony Optimization Algorithm to Solve the Periodic Capacitated Arc Routing Problem with Continuous Moves

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Guilherme V. Batista ◽  
Cassius T. Scarpin ◽  
José E. Pécora ◽  
Angel Ruiz
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Arc Routing ◽  
Ant Colony Optimization Algorithm ◽  
Routing Problem ◽  
Capacitated Arc Routing Problem ◽  
Railroad Network ◽  
Local Search Procedure ◽  
Capacitated Arc Routing

This paper describes a variant of the Periodic Capacitated Arc Routing Problem for inspections in a railroad network. Inspections are performed by vehicles over a time horizon on which some stretches need evaluation more frequently than others due to its use. Each car can evaluate one stretch per day without being attached to a depot; at each day, the shift may start and end at different locations. This characterizes the problem as the Periodic Capacitated Arc Routing Problem with Continuous Moves in which firstly the delays on attendances are minimized and, second, the displacement costs. We present a mathematical model and an Ant Colony Optimization algorithm to solve the problem. The use of a local search procedure and some principles of Granular Tabu Search is crucial for the algorithm’s performance. The numerical results are promising, especially for critical situations where the arcs’ needs are close to the total vehicles’ capacity.

An improved ant colony optimization for the multi-trip Capacitated Arc Routing Problem

2019 ◽  
Vol 77 ◽  
pp. 457-470 ◽  
Author(s):  
Erfan Babaee Tirkolaee ◽  
Mehdi Alinaghian ◽  
Ali Asghar Rahmani Hosseinabadi ◽  
Mani Bakhshi Sasi ◽  
Arun Kumar Sangaiah
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Arc Routing ◽  
Routing Problem ◽  
Capacitated Arc Routing Problem ◽  
Capacitated Arc Routing

A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management

2019 ◽  
Vol 38 (2) ◽  
pp. 156-172 ◽  
Author(s):  
Erfan Babaee Tirkolaee ◽  
Iraj Mahdavi ◽  
Mir Mehdi Seyyed Esfahani ◽  
Gerhard-Wilhelm Weber
Keyword(s):  
Waste Management ◽  
Solid Waste ◽  
Ant Colony Optimization ◽  
Solid Waste Management ◽  
Ant Colony ◽  
Arc Routing ◽  
Routing Problem ◽  
Capacitated Arc Routing Problem ◽  
Urban Solid Waste ◽  
Capacitated Arc Routing

Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max–min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters’ values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.

scholarly journals Open capacitated arc routing problem by hybridized ant colony algorithm

2021 ◽  
Author(s):  
Bilal Kanso ◽  
Ali Kansou ◽  
Adnan Yassine
Keyword(s):  
Ant Colony Algorithm ◽  
Search Algorithm ◽  
Ant Colony ◽  
Arc Routing ◽  
Local Search Algorithm ◽  
Routing Problem ◽  
Capacitated Arc Routing Problem ◽  
Cost Distance ◽  
Benchmark Instances ◽  
Capacitated Arc Routing

The Open Capacitated Arc Routing Problem OCARP is a well-known NP-hard real-world combinatorial optimization problem. It consists of determining optimal routes for vehicles in a given service area at a minimal cost distance. The main real application for OCARP is the Meter Reader Routing Problem (MRRP). In MRRP problem, each worker in the electric (or gas) company must visit and read the electric (or gas) meters to a set of customers by starting his route from the first customer on his visit list and finishing with the last one. The worker leaves where he wants once all the associated customers have been visited. In this paper, a meta-heuristic called an Hybridized Ant Colony Algorithm (HACA) is developed and hybridized with a local search algorithm that involves the 2-opt, Swap, Relocate and Cross-exchange moves to solve OCARP problem. Computational results conducted on five different sets of OCARP-instances showed that our proposed algorithm HACA has reached good and competitive results on  benchmark instances for the problem.

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