Abstract The flexible job-shop scheduling problem (FJSP) is a critical model in manufacturing systems that assigns operations from different jobs to various machines. However, optimizing multiple targets during the production process always necessary. While non-dominated sorting genetic algorithm (NSGA-II) an effective method solve multi-objective FJSP, it can have main drawbacks of converging ...

An energy-efficient Wireless Sensor Network (WSN) design often requires the decision of optimal locations (deployment) and power assignments of the sensors to be densely deployed in an area of interest. In the literature, no attempts have beenmade on optimizing both decision variables formaximizing the network coverage and lifetime objectives,whilemaintaining the connectivity constraint, at the...

This paper presents an application of elitist non-dominated sorting genetic algorithm (NSGA-II) for solving a multi-objective reactive power market clearing (MO-RPMC) model. In this MO-RPMC model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and voltage stability enhancement index (VSEI) are optimized simultaneous...

A multi-objective optimization problem (MOP) is often found in real-world optimization problem. Among various multiobjective optimization techniques, multi-objective evolutionary algorithm (MOEA) is highlighted as a good candidate due to its flexibility, feasibility, and its ability to handle multiple solutions. Among various MOEAs, we analyze 2MOEA which can achieve good convergence and divers...

In wireless sensor networks (WSNs), prototyping systems facilitate the realization of real node deployment, enabling to test new algorithms, proto‐ cols, and networking solutions. This paper investigates the 3D indoor redeploy‐ ment problem in WSNs by finding the positions where nodes should be added in order to improve an initial deployment while optimizing different objectives. For this purpo...

Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...

This paper considers two-level assembly systems whose lead times of components are stochastic with known discrete random distributions. In such a system, supply planning requires determination of release dates of components at level 2 in order to minimize expected holding cost and to maximize customer service. Hnaien et al. [Hnaien F, Delorme X, Dolgui A. Multi-objective optimization for invent...

As one of the most challenging combinatorial optimization problems in scheduling, the resource-constrained project scheduling problem (RCPSP) has attracted numerous scholars’ interest resulting in considerable research in the past few decades. However, most of these papers focused on the single objective RCPSP; only a few papers concentrated on the multi-objective resource-constrained project s...

nowadays urban sanitary landfill compatible with environmental principles and in line with sustainable development is a necessity. in this paper for the purpose of determining appropriate sanitary landfill sites in kohgilooye & boyerahmad province, , many data layers were used including: slope, land cover, distance to main roads, distance to cities & villages, geology, surface water network, di...

As the share of wind energy in power system increases, consideration of these resources in power system planning, particularly in Transmission Expansion Planning (TEP) is becoming more and more important. In this paper, a Probabilistic Multi-Objective Transmission Expansion Planning (PMO-TEP) is presented to find the optimal node for connecting the large scale distant wind farm to the network f...