Tabu Search Metaheuristic Embedded in Adaptive Memory Procedure for the Profitable Arc Tour Problem (original) (raw)
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2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
This paper describes a tabu search heuristic embedded in adaptive memory procedure for the Profitable Arc Tour Problem (PATP). The PATP is a variant of the well-known Vehicle Routing Problem in which a set of vehicle tours are constructed. The objective is to find in the graph a set of cycles that maximize the collection of profits minus travel costs, which is in turn subject to constraints limiting the length of cycles that profit is available on arcs. We propose a tabu search algorithm for the solution of the PATP. The tabu search heuristic is embedded in an adaptive memory procedure that alternates between small and large neighborhood stages during the solution improvements phase. Computational experiments are made in randomly generated instances given by .
Metaheuristics optimization via memory to solve the profitable arc tour problem
In this paper we propose a metaheuristic optimization via memory to solve the Profitable Arc Tour Problem (PATP). The PATP is a variant of the well-known Vehicle Routing Problem in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the vehicle tours that maximize the collection of profits minus travel costs, subject to constraints limiting the length of cycles that profit is available on arcs. Computational experiments show that our algorithm provides good results in terms of quality of solution and completion processing times.
Adaptive Memory Procedure to solve the Profitable Arc Tour Problem
Int. J. Comb. Optim. Probl. Informatics, 2010
In this paper we propose an Adaptive Memory Procedure to solve the Profitable Arc Tour Problem (PATP). The PATP is a variant of the well-known Vehicle Routing Problems in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the vehicle tours that maximize the collection of profits minus travel costs, subject to constraints limiting the length of cycles that profit is available on arcs. Computational experiments show that our algorithms provide good results in terms of quality of solution and running times.
Hybrid metaheuristics for the profitable arc tour problem
Journal of the Operational Research Society, 2011
The profitable arc tour problem is a variant in the vehicle routing problems. It is included in the family of the vehicle routing with profit problems in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the vehicle tours that maximize the collection of profits minus travel costs, subject to constraints limiting the length of cycles that profit is available on arcs. To solve this variant we adopted two metaheuristics based on adaptive memory. We show that our algorithms provide good results in terms of solution quality and running times.
A tabu search heuristic for the undirected selective travelling salesman problem
European Journal of Operational Research, 1998
The undirected Selective Travelling Salesman Problem (STSP) is defined on a graph G= (V, E) with positive profits associated with vertices, and distances associated with edges. The STSP consists of determining a maximal profit Hamiltonian cycle over a subset of V whose length does not exceed a preset limit L. We describe a tabu search (TS) heuristic for this problem. The algorithm iteratively inserts clusters of vertices in the current tour or removes a chain of vertices. Tests performed on randomly generated instances with up to 300 vertices show that the algorithm consistently yields near-optimal solutions.
A reactive tabu search for the vehicle routing problem
Journal of the Operational Research Society, 2006
A heuristic approach based on a hybrid operation of reactive tabu search (RTS) and adaptive memory programming (AMP) is proposed to solve the vehicle routing problem with backhauls (VRPB). The RTS is used with an escape mechanism which manipulates different neighbourhood schemes in a sophisticated way in order to get a continuously balanced intensification and diversification during the search process. The adaptive memory strategy takes the search back to the unexplored regions of the search space by maintaining a set of elite solutions and using them strategically with the RTS. The AMP feature brings an extra robustness to the search process that resulted in early convergence when tested on most of the VRPB instances. We compare our algorithm against the best methods in the literature and report new best solutions for several benchmark problems.
A Tabu Search Heuristic for the Vehicle Routing Problem
Management Science, 1994
The purpose of this paper is to describe TABUROUTE, a new tabu search heuristic for the vehicle routing problem with capacity and route length restrictions. The algorithm considers a sequence of adjacent solutions obtained by repeatedly removing a vertex from its current route and reinserting it into another route. This is done by means of a generalized insertion procedure previously
Behaviour of a Hybrid ILS Heuristic on the Capacitated Profitable Tour Problem
2018
In the present paper, we study the behaviour of a hybrid Iterative Local Search heuristic (ILS). A Large Neighborhood Search heuristic (LNS) and a Variable Neighborhood Descent with Random neighborhood ordering (RVND) are used in the local search phase of the proposed ILS. The approach is evaluated on a well-known variant of the Vehicle Routing Problem (VRP) called Capacitated Profitable Tour Problem (CPTP). In this variant, the vehicles are no longer required to visit all the customers. However, a specific profit is obtained each time a customer is visited. The goal of the CPTP is to design routes with maximum difference between collected profits and routing costs, which satisfy the capacity constraint of the vehicles. The experimental study consists in comparing different combinations of ILS, LNS and RVND. The computational results show that the hybridization of the three heuristics leads to better solutions. Furthermore, comparisons with a Variable Neighborhood Search and two Tabu Searches from the literature indicates that our hybrid approach is competitive.
A TABU search heuristic for the team orienteering problem
Computers & Operations Research, 2005
This paper describes a tabu search heuristic for the Team Orienteering Problem (TOP). The TOP is a variant of the well-known Vehicle Routing Problem in which a set of vehicle tours are constructed such that the total collected reward received from visiting a subset of customers is maximized and the length of each vehicle tour is restricted by a pre-speciÿed limit. The tabu search heuristic is embedded in an adaptive memory procedure that alternates between small and large neighborhood stages during the solution improvement phase. Both random and greedy procedures for neighborhood solution generation are employed and infeasible, as well as feasible, solutions are explored in the process. Results from computational experiments conducted on a set of published test problems show that the proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the TOP.
The Profitable Arc Tour Problem: Solution with a Branch-and-Price Algorithm
Transportation Science, 2005
In this article, we introduce a new arc routing problem that we call the profitable arc tour problem. This problem is defined on a graph in which profits and travel costs are associated with the arcs. The objective is to find a set of cycles in the graph that maximizes the collection of profit minus travel costs, subject to constraints limiting the number of times that profit is available on arcs and the maximal length of cycles. The problem is related both to constrained flow problems and to vehicle-routing problems. We tackle it from this standpoint and propose a branch-and-price algorithm for its solution. In the column-generation phase, the issue of the collection decisions while traveling through the arcs is addressed. In the branching phase, the fact that viewing solutions in terms of flow variables regularly induces an integer flow matrix leads us to introduce a branching method called the flow-splitting method. Finally, the relationships of this problem with constrained flow...