A selection hyper-heuristic is a high level search methodology which operates over a fixed set of low level heuristics. During the iterative search process, a heuristic is selected and applied to a candidate solution in hand, producing a new solution which is then accepted or rejected at each step. Selection hyper-heuristics have been increasingly, and successfully, applied to single-objective ...

Abstract. The paper focuses its attention on solving Multi-objective intuitionistic fuzzy linear programming problem and Multi-objective intuitionistic fuzzy linear fractional programming problem by using weighting factor in which the constraints and the cost coefficients are intuitionistic fuzzy numbers. Weighting factor is used to convert problems that are multi-objective into single objectiv...

Hyper-Heuristics is a high-level methodology for selection or automatic generation of heuristics for solving complex problems. Despite the hyper-heuristics success, there is still only a few multi-objective hyper-heuristics. Our approach, MOEA/D-HH, is a multi-objective selection hyper-heuristic that expands the MOEA/D framework. It uses an innovative adaptive choice function proposed in this w...

Ontology alignment is an essential and complex task to integrate heterogeneous ontology. The meta-heuristic algorithm has proven be effective method for ontology alignment. However, it only applies the inherent advantages of meta-heuristics rarely considers execution efficiency, especially multi-objective model. performance such optimization models mostly depends on well-distributed fast-conver...

This paper considers a flowshop scheduling problem of a manufacturing cell that contains families of jobs whose setup times are dependent on the manufacturing ............ sequence of the families. Two objectives, namely the makespan and total flow time, have been considered simultaneously in this work. Since minimization of each of these two objectives is an NpHard problem, a Multi-Objective G...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. one type of scheduling problems is just-in-time (jit) scheduling and in this area, motivated by jit manufacturing, this study investigates a mathematical model for...

Scheduling and resource allocation to optimize performance criteria in multi-cluster heterogeneous environments is known as an NP-hard problem, not only for the resource heterogeneity, but also for the possibility of applying co-allocation to take advantage of idle resources across clusters. A common practice is to use basic heuristics to attempt to optimize some performance criteria by treatin...