The nondominated sorting genetic algorithm with elitism (NSGA-II) is widely used due to its good performance on solving multiobjective optimization problems. In each iteration of NSGA-II, truncation selection is performed based on the rank and crowding distance of each solution. There are, however, drawbacks in this process. These drawbacks to some extent cause overlapping solutions in the popu...

As a new model of networked manufacturing services, cloud (CMfg) aims to allocate enterprise resources, realize rational utilization and adapt increasingly complex user needs. However, previous studies on service composition optimal selection (SCOS) in CMfg environments do not incorporate carbon emissions into the quality (QoS) evaluation indicators. Therefore, SCOS for under low-carbon environ...

electric wheelchairs (ew) experience various terrains surfaces and slopesas well asoccupants with diverse weights. this, in turn, imparts a substantial amount of perturbation to the ewdynamics. in this paper we make use of a two-degree-of-freedom control architecture called disturbance observer (dob) which reduces sensitivity to model uncertainties while enhancing rejection of disturbances caus...

Regarding the complicated flexible job-shop scheduling problem, it is not only required to get optimal solution of problem but also ensure low-carbon and environmental protection. Based on NSGA-II algorithm, this article proposes an improved adaptive non-dominated sorting genetic algorithm with elite strategy (IA-NSGA-ES). Firstly, constructive heuristic introduced in initial population phase, ...

In this paper, we propose a multi-objective evolutionary metaheuristic approach based on the Pareto Ant Colony Optimization (P-ACO) and non-dominated genetic sorting algorithms (NSGA II NSGA III) to solve bi-objective portfolio optimization problem. P-ACO is used select best assets composing efficient portfolio. Then, III are separately find proportional weights of budget allocated selected The...

A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...

Background: The recent progress and achievements in the advanced, accurate, and rigorously evaluated algorithms has revolutionized different aspects of the predictive microbiology including bacterial growth.Objectives: In this study, attempts were made to develop a more accurate hybrid algorithm for predicting the bacterial growth curve which can also be ...

A new model and solution for the energy minimizing vehicle routing problem with time windows (EVRPTW) and customers’ priority is presented in this paper. In this paper unlike prior attempts to minimize cost by minimizing overall traveling distance, the model also incorporates energy minimizing which meets the latest requirements of green logistics. This paper includes the vehicles load as an ad...

Surface grinding is the most common process used in the manufacturing sector to produce smooth finish on flat surfaces. Surface quality and metal removal rate are the two important performance characteristics to be considered in the grinding process. The economics of the machining process is affected by several factors such as abrasive wheel grade, wheel speed, depth of cut, table speed and mat...