Sequential and parallel local search for the time-constrained travelling salesman problem

Local search has proven to be an effective solution approach for the traveling salesman problem. We consider variants of the TSP in which each city is to be visited within one or more given time windows. The travel times are symmetric and satisfy the triangle inequality; therobjective is to minimize the tour duration. We develop efficient sequential and parallel algorithms for the verification of local optimality of a tour with respect to k-exchanges

Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art

Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP

Parallel ACO with a Ring Neighborhood for Dynamic TSP

The current paper introduces a new parallel computing technique based on ant colony optimization for a dynamic routing problem. In the dynamic traveling salesman problem the distances between cities as travel times are no longer fixed. The new technique uses a parallel model for a problem variant that allows a slight movement of nodes within their Neighborhoods. The algorithm is tested with success on several large data sets.Comment: 8 pages, 1 figure; accepted J. Information Technology Researc

A hybrid heuristic solving the traveling salesman problem

This paper presents a new hybrid heuristic for solving the Traveling Salesman Problem, The algorithm is designed on the frame of a general optimization procedure which acts upon two steps, iteratively. In first step of the global search, a feasible tour is constructed based on insertion approach. In the second step the feasible tour found at the first step, is improved by a local search optimization procedure. The second part of the paper presents the performances of the proposed heuristic algorithm, on several test instances. The statistical analysis shows the effectiveness of the local search optimization procedure, in the graphical representation.peer-reviewe

A parallel implementation of ant colony optimization

Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for optimization problems. As it is a population-based technique that examines numerous solution options at each step of the algorithm, there are a variety of parallelization opportunities. In this paper, several parallel decomposition strategies are examined. These techniques are applied to a specific problem, namely the travelling salesman problem, with encouraging speedup and efficiency results.Full Tex