The hypergraph transversal problem has been intensively studied, from both a theoretical and a practical point of view. In particular, its incremental complexity is known to be quasi-polynomial in general and polynomial for bounded hypergraphs. Recent applications in computational biology however require to solve a generalization of this problem, that we call bi-objective transversal problem. T...

Pareto local search (PLS) is an extension of iterative improvement methods for multi-objective combinatorial optimization problems and an important part of several state-of-the-art multi-objective optimizers. PLS stops when all neighbors of the solutions in its solution archive are dominated. If terminated before completion, it may produce a poor approximation to the Pareto front. This paper pr...

The paper introduces a genetic algorithms based elevator group control system utilising new approaches to multiobjective optimisation in a dynamically changing process control environment. The problem of controlling a group of elevators as well as the basic principles of the existing single-objective genetic elevator group control method are described. The foundations of the developed multi-obj...

This paper presents a bi level large scale multi objective quadratic programming problem (BLLSMOQPP) with fuzzy parameters in the objective functions problem. In the first phase convert the fuzzy parameters of the problem to equivalent crisp problem to make it easy in solving. In the second phase use Taylor series to convert the quadratic problem to linear problem to be easy for solving with th...

Conflicting objectives becomes a common issue in many supply chain network optimization problems. In this paper, a new model is formulated to design a green supply chain network through a new mixed integer linear programming problem. Uncertain demand and stochastic environmental respect levels are the main parameters of the formulation. The first objective function minimizes the cost of the sup...

In this paper a bimodal discrete urban road network design problem with bus and car modes is investigated. The problem consists of decision making for lane addition to the existing streets, new street constructions, converting some two-way streets to one-way streets, lane allocation for two-way streets, and the allocation of some street lanes for exclusive bus lanes. Two objectives are consider...

The nonnegative matrix factorization (NMF) is a powerful data analysis and dimensionality reduction technique. So far, the NMF has been limited to a single-objective problem in either its linear or nonlinear kernel-based formulation. This paper presents a novel bi-objective NMF model based on kernel machines, where the decomposition is performed simultaneously in both input and feature spaces. ...

To obtain a better understanding of the trade-offs between various objectives, Bi-Objective Integer Programming (BOIP) algorithms calculate the set of all non-dominated vectors and present these as the solution to a BOIP problem. Historically, these algorithms have been compared in terms of the number of single-objective IPs solved and total CPU time taken to produce the solution to a problem. ...

In this paper, we propose an extension of the classical location area planning (LAP) problem in the wireless telephony system including additional objectives and constraints. The bi-objective location area planning (BOLAP) problem considers the minimisation of both distance costs between base A bi-objective location area planning for wireless phone network 343 transceiver stations and the base ...

an integrated model considers all parameters and elements of different deficiencies in one problem. this paper presents a new integrated model of a supply chain that simultaneously considers facility location, vehicle routing and inventory control problems as well as their interactions in one problem, called location-routing-inventory (lri) problem. this model also considers stochastic demands ...