Abstract Sparse large-scale multi-objective optimization problems (LSMOPs) widely exist in real-world applications, which have the properties of involving a large number decision variables and sparse Pareto optimal solutions, i.e., most these solutions are zero. In recent years, LSMOPs attracted increasing attentions evolutionary computation community. However, all recently tailored algorithms ...

mobile-ad-hoc-networks (manets) are self-configuring networks of mobile nodes, which communicate through wireless links. the infrastructure of a mobile ad hoc network (manet) has no routers for routing, and all nodes must share the same routing protocol to assist each other when transmitting messages. the main issues in manets include the mobility of the network nodes, the scarcity of computati...

Multi-objective optimization (MO) has been an active area of research in the last two decades. In multi-objective genetic algorithm (MOGA), the quality of newly generated offspring of the population will directly affect the performance of finding the Pareto optimum. In this paper, an improved MOGA, named SMGA, is proposed for solving multi-objective optimization problems. To increase efficiency...

Evolutionary Computation (EC) is the field of computational systems that use ideas and get inspiration from natural evolution [1]. Genetic Algorithms (GA) fall into the category of EC. GA are a type of search and optimization algorithm based on the mechanisms of genetics and natural selection. The canonical form of GA encodes each candidate solution to a given problem as a binary, integer, or r...

This paper presents the investigation of an evolutionary multi-objective simulated annealing algorithm with variable neighborhoods to solve the multi-objective multicast routing problems in telecommunications. The hybrid algorithm aims to carry out a more flexible and adaptive exploration in the complex search space by using features of the variable neighborhood search to find more non-dominate...

The objective of this paper is to develop matrix games with pay-offs of triangular hesitant fuzzy elements (THFEs). To solve such games, a new methodology has been derived based on the notion of weighted average operator and score function of THFEs. Firstly, we formulate two non-linear programming problems with THFEs. Then applying the score function of THFEs, we transform these two problems in...

this paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequence-dependent setup times that minimizes the weighted mean completion time and the weighted mean tardiness time. for solving this multi-objective model, we develop a fuzzy multi-objective linear programming (fmolp) model. in this problem, a proposed fmolp method is applied with respect to the o...