An interactive approach to solve a multi-objective covering-routing problem considering critical areas

2011 ◽  
Author(s):  
Maria Jose Pinto Lamosa ◽  
Daniel Merli Lamosa ◽  
Monica Maria De Marchi
Keyword(s):  
Interactive Approach ◽  
Routing Problem ◽  
Multi Objective ◽  
Critical Areas

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Solving Multi-Objective Multicast Routing Problem Using a New Hybrid Approach

2018 ◽  
Vol 9 (4) ◽  
pp. 22-36
Author(s):  
Mohammed Mahseur ◽  
Abdelmadjid Boukra ◽  
Yassine Meraihi
Keyword(s):  
Multicast Routing ◽  
Hybrid Approach ◽  
Bat Algorithm ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Multi Objective ◽  
Strength Pareto Evolutionary Algorithm ◽  
Quality Of Service Parameters

Multicast routing is the problem of finding the spanning tree of a set of destinations whose roots are the source node and its leaves are the set of destination nodes by optimizing a set of quality of service parameters and satisfying a set of transmission constraints. This article proposes a new hybrid multicast algorithm called Hybrid Multi-objective Multicast Algorithm (HMMA) based on the Strength Pareto Evolutionary Algorithm (SPEA) to evaluate and classify the population in dominated solutions and non-dominated solutions. Dominated solutions are evolved by the Bat Algorithm, and non-dominated solutions are evolved by the Firefly Algorithm. Old and weak solutions are replaced by new random solutions by a process of mutation. The simulation results demonstrate that the proposed algorithm is able to find good Pareto optimal solutions compared to other algorithms.

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