Hybrid sorting immune simulated annealing technique (HSISAT), a Meta heuristic is proposed for solving the multi objective flexible job-shop scheduling problem (FJSP). The major objectives are distributing the time of machines among the set of operations and scheduling them to minimize the criterion (makespan, total workload and maximum workload). The processing time is sorted for isolating the...

In this paper, we consider the problem of scheduling n independent jobs on m uniform parallel machines such that total weighted completion time is minimized. We present two meta-heuristics and two hybrid meta-heuristics to solve this problem. Based on a set of instances, a comparative study has been realized in order to evaluate these approaches.

one of the most important extensions of the capacitated vehicle routing problem (cvrp) is the vehicle routing problem with simultaneous pickup and delivery (vrpspd) where customers require simultaneous delivery and pick-up service. in this paper, we propose an effective ant colony optimization (eaco) which includes insert, swap and 2-opt moves for solving vrpspd that is different with common an...

The Vehicle Routing Problem (VRP) is a NP-hard and Combinatorial optimization problem. Combinatorial optimization problem can be viewed as searching for best element in a set of discrete items, which can be solved using search algorithm or meta heuristic. In this work, VRP is solved using population based search algorithm, Particle Swarm Optimization (PSO) with crossover and mutation operators....

A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the traditional genetic recombination operators. One of the search operators is designed to repair unfeasible timetables produced by the initialization procedure and the mutation operator. The other search operator implemen...

Optimization of the complete manufacturing and supply process has become a critical ingredient for gaining a competitive advantage. This article provides a unified mathematical framework for modeling manufacturing cell configuration and raw material supplier selection in a two-level supply chain network. The commonly used manufacturing design parameters along with supplier selection and a subco...

This paper presents a Greedy Randomized Adaptive Search Procedure (GRASP) for the Prize-Collecting Covering Tour Problem (PCCTP), which is problem of finding route traveling teams that provide services to communities geographically distant from large urban locations. We devised novel hybrid heuristic by combining reactive extension GRASP with Random Variable Neighborhood (VND) meta-heuristic pu...

The purpose of this article is to review the literature on the topic of deterministic vehicle routing problem (VRP) and to give a review on the exact and approximate solution techniques. More specifically the approximate (meta-heuristic) solution techniques are classified into: tabu search, simulated annealing, genetic algorithm, evolutionary algorithm, hybrid algorithm, and Ant Colony Optimiza...

The G3-PCX genetic algorithm is compared with hybrid meta-heuristic approaches for solving the forward kinematics problem of the 6-6 general parallel manipulator. The G3-PCX shows improvements in terms of accuracy, response time and reliability. Several experiments confirm solving the given problem in less than 1 second. It also reports all the 16 unique real solutions which are verified by an ...

CODEQ is a new, population-based meta-heuristic algorithm that is a hybrid of concepts from chaotic search, opposition-based learning, differential evolution and quantum mechanics. CODEQ has successfully been used to solve different types of problems (e.g. constrained, integer-programming, engineering) with excellent results. In this paper, CODEQ is used to train feed-forward neural networks. T...