Metaheuristics for solving the biobjective single‐path multicommodity communication flow problem

Abstract

Single‐path multicommodity flow problem (SMCFP) is a well‐known combinatorial optimization problem, in which the flow of each commodity can be transmitted using only one path linking its destination to an appropriate origin within the addressed network. In this paper, we study the SMCFP in a multiobjective context by considering the simultaneous optimization of paths' delay and average reliability. The network is modeled as a finite set of nodes that can communicate using preestablished connections where each connection is characterized by a capacity, a lead time, and a reliability. A node can be an information producer or/and information consumer. The contention problem is solved by assigning a path and a dedicated bandwidth to each flow. The problem is formulated as a biobjective nonlinear optimization problem. This biobjective problem has not been considered in the literature. We design three alternative procedures for approximating the Pareto front. We proposed an MGA based on NSGA‐II, a multiobjective variable neighborhood search and a new distance‐based hybrid metaheuristic. The hybridization integrates a local search into the framework of genetic algorithm to effectively drive the search toward a better approximating of the Pareto front. The propounded algorithms' efficiencies are experimentally investigated on a test bed of instances applied to a planar and a grid network. A comparative study is conducted based on different multiobjective performance indicators.

An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

“…These tests did not deal with the total number of instances to avoid the exhaustive execution of the algorithms, as appointed by Masri et al. (). For testing each configuration, nine instances were chosen at random, totalizing 252 test instances.…”

“…In Masri et al. (), a hybrid method that uses MO‐VNS for exploring and intensifying the search in specific regions is applied to solve the single‐path multicommodity communication flow problem. López‐Sánchez et al.…”

Randomized rounding algorithms for large scale unsplittable flow problems

“…As introduced above, it is NP-hard to find an optimal solution or even to give a constant-factor approximation to the unsplittable flow problem. Thus, the literature investigated various randomized search procedures such as genetic algorithms (Cox 1991;Masri et al 2019), tabu search (Anderson et al 1993;Laguna and Glover 1993;Xu et al 1997), local search and GRASP (Santos et al 2010(Santos et al , 2013aAlvelos and Valério de Carvalho 2007;Masri et al 2015Masri et al , 2019 or ant colony optimization (Li et al 2010;Masri et al 2011). One of the major difficulties encountered when solving the unsplittable flow problem with a meta-heuristic is to efficiently create useful paths for the commodities.…”

“…As stated in Masri et al (2019), no standard benchmark of instances is present in the literature for the unsplittable flow problem, especially for large instances. Indeed, most works use small graphs (less than 50 nodes) on which they manually generate a set of commodities.…”

On the reliability estimation of stochastic binary systems

“…Masri et al. (2019) discuss a network optimization problem where the nodes can communicate using a predetermined set of connections characterized by a capacity, a lead time, and a reliability, developing a multiobjective model to optimize both delays and average reliability.…”