A Meta-Heuristic Algorithm Combining Between Tabu and Variable Neighborhood Search for the Minimum Latency Problem

Ban, Ha-Bang; Nguyen, Duc Nghia

doi:10.3233/fi-2017-1596

Cited by 13 publications

(15 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our algorithm gives much better solutions than those of GVNS-1 [17], GRASP-VND and GRASP-VNS [19] for all instances. In comparison with GVNS-2 [17], and TS [3], for most cases, our algorithm gives the same results.…”

Section: Results and Comparative Analysismentioning

confidence: 64%

“…Our experiments not only prove these expectations but also indicate that this approach finds the new best known solutions in the 303 instances in comparison with thestate-of-art metaheuristic. Moreover, our experiments show that the methods designed for the DMP [3,17,19] may not be adapted easily to solve the CRDMP since the optimal solutions for the DMP are infeasible solutions for the CRDMP. Therefore, it is important for developing a metaheuristic for the CRDMP .…”

Section: Dicussionsmentioning

confidence: 99%

“…Currently, there is no exact algorithm in the literature that can solve the problem with up to 100 vertices. Therefore, we use the metaheuristic in [3] to obtain near-optimal solutions. All instances are available in the online supplement to this paper at 2 .…”

Section: Benchmark Instancesmentioning

confidence: 99%

See 2 more Smart Citations

An Efficient ACO+RVND for Solving the Resource-Constrained Deliveryman Problem

Bang

2020

MIC ICT Research Journal

View full text Add to dashboard Cite

In this paper, Resource-Constrained Deliveryman Problem (RCDMP) is introduced. The RCDMP problem deals with finding a tour with minimum waiting time sum so that it consumes not more than the $R_{max}$ unites of the resources, where $R_{max}$ is some constant. Recently, an algorithm developed in a trajectory-based metaheuristic has been proposed. Since the search space of the problem is a combinatorial explosion, the trajectory-based sequential can only explore a subset of the search space, therefore, they easily fall into local optimal in some cases. To overcome the drawback of the current algorithms, we propose a population-based algorithm that combines an Ant Colony Algorithm (ACO), and Random Variable Neighborhood Descent (RVND). In the algorithm, ACO explores the promising solution areas while RVND exploits them with the hope of improving a solution. Extensive numerical experiments and comparisons with the state-of-the-art metaheuristic algorithms in the literature show that the proposed algorithm reaches better solutions in many cases.

show abstract

Section: Results and Comparative Analysismentioning

confidence: 64%

Section: Dicussionsmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient ACO+RVND for Solving the Resource-Constrained Deliveryman Problem

Bang

2020

MIC ICT Research Journal

View full text Add to dashboard Cite

show abstract

“…Specifically, for the MLP problem, in Table 6, our algorithm outperforms the other algorithms in Ban and Nguyen (2010); Mafort and Ochi (2016) and Salehipour et al (2011). In comparison with the other algorithms (Ban 2017a(Ban , 2017bSilva et al, 2012), our algorithm finds solutions at least as well as for the most of instances. In addition, our algorithm finds the optimal solutions for the instances with up to 100 vertices in several seconds in Table 7.…”

Section: Experimental Results For Mlp Instancesmentioning

confidence: 84%

Variable neighbourhood search-based algorithm to solve the minimum back-walk-free latency problem

Ban¹

2021

IJCAT

View full text Add to dashboard Cite

The Minimum Back-Walk-Free Latency Problem (MBLP) is an extension of the Minimum Latency Problem (MLP). It aims to find a tour with minimum latency while ignoring the back-walking costs. One of the justifications for ignoring the back-walking costs is in applications of message broadcasting for mobile devices. Obviously, the MBLP is NP-hard problem because it is a particular variant of MLP. Therefore, metaheuristic needs to be developed to provide near-optimal solutions within a short computation time. However, the main issue of metaheuristics is that they fall into local optima in some cases since the search space of the problem is combinatorial explosion. To overcome the drawback, we propose a metaheuristic algorithm combined between the Variable Neighbourhood Search (VNS) and shaking technique to solve the problem. The aim of VNS is to generate diverse neighbourhoods by using various neighbourhood searches while the shaking technique guides the search towards an unexplored part of the solution space. Moreover, a technique called Adaptive Memory (AM) is applied to balance between diversity and intensification. The computational results show that the effectiveness and efficiency of the proposed algorithm are comparable with the state-of-the-art algorithms.

show abstract

“…The Traveling Repairman Problem (TRP) or Minimum Latency Problem (MLP) has been studied in a number of previous work [1,2,3,4,5,6,7,8,9,14]. It has arised many practical applications, e.g., whenever repairman or servers have to accommodate a set of requests so as to minimize their total (or average) waiting time [1,8,14].…”

Section: Introductionmentioning

confidence: 99%

A GRASP+VND Algorithm for the Multiple Traveling Repairman Problem with Distance Constraints

Ban

2018

JCC

View full text Add to dashboard Cite

Abstract. Multiple Traveling Repairmen Problem (MTRP) is a class of NP-hard combinatorial optimization problems. In this paper, an other variant of MTRP, also known as Multiple Traveling Repairmen Problem with Distance Constraint (MTRPD), is introduced. In MTRPD problem, a fleet of vehicles serves a set of customers. Each vehicle which starts from the depot is not allowed to travel any distance longer than a limit and each customer must be visited exactly once. The goal is to find the order of customer visits of all vehicles that minimizes the sum of all vertices' waiting time. To the best of our knowledge, the problem has not been studied much previously, even though it is a natural and practical extension of the Traveling Repairman Problem or Multiple Traveling Repairmen Problem case. In our work, we propose a metaheuristic algorithm which is mainly based on the principles of Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) to solve the problem. The GRASP is used to build an initial solution which is good enough in a construction phase. In a cooperative way, the VND is employed to generate diverse neighborhoods in an improvement phase, therefore, it can help the search escape from local optimal. Extensive numerical experiments on 321 benchmark instances show that our algorithm can find the optimal solutions with up to 50 vertices in several instances. For larger instances, our algorithm obtains provably near-optimal solutions, even for large instances.

show abstract

A Meta-Heuristic Algorithm Combining Between Tabu and Variable Neighborhood Search for the Minimum Latency Problem

Cited by 13 publications

References 10 publications

An Efficient ACO+RVND for Solving the Resource-Constrained Deliveryman Problem

An Efficient ACO+RVND for Solving the Resource-Constrained Deliveryman Problem

Variable neighbourhood search-based algorithm to solve the minimum back-walk-free latency problem

A GRASP+VND Algorithm for the Multiple Traveling Repairman Problem with Distance Constraints

Contact Info

Product

Resources

About