This paper provides a test method to make a fair comparison between different heuristics in structure optimization. When statistical methods are applied to the structural optimization (namely heuristics or meta-heuristics with several tunable parameters and starting seeds), the "one problem - one result" is extremely far from the fair comparison. From statistical point of view, the minimal requ...

Hyper-heuristics are (meta-)heuristics that operate at a high level to choose or generate a set of low-level (meta-)heuristics to solve difficult search and optimisation problems. Evolutionary algorithms are well-known natureinspired meta-heuristics that simulate Darwinian evolution. In this article, we introduce an evolutionary-based hyper-heuristic in which a set of low-level heuristics compe...

Meta-heuristics have received increasing attention in recent years. The present article introduces a novel method in such a class that distinguishes a number of artificial search agents called players within two teams. At each iteration, the active player concerns some other players in both teams to construct its special movements and to get more score. At the end of some iterations (like quart...

periodic vehicle routing problem focuses on establishing a plan of visits to clients over a given time horizon so as to satisfy some service level while optimizing the routes used in each time period. This paper presents a new effective heuristic algorithm based on data mining tools for periodic vehicle routing problem (PVRP). The related results of proposed algorithm are compared with the resu...

aggregate production planning (app) is one of the most important issues carried out in manufacturing environments which seeks efficient planning, scheduling and coordination of all production activities that optimizes the company's objectives. in this paper, we develop a mixed integer linear programming (milp) model for an integrated aggregate production planning system with closed loop su...

this paper proposes a new mixed integer programming model for multi-item capacitated lot-sizing problem with setup times, safety stock and demand shortages in closed-loop supply chains. the returned products from customers can either be disposed or be remanufactured to be sold as new ones again. due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (sa) al...

In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...

hub covering problem (hlp) is a very popular areas of research for its wide ranges of applications in different service or manufacturing industries. this paper considers a bi-objective hub covering location problem with congestion. the objectives minimize the total transportation cost and the total waiting time for all hobs, respectively. the resulted multi-objective decision-making problem is ...

Meta-heuristics are methods that sit on top of local search algorithms. They perform the function of avoiding or escaping a local optimum and/or premature convergence. The aim of this paper is to survey, compare and contrast meta-heuristics for local search. First, we present the technique of local search (or hill climbing as it is sometimes known). We then present a table displaying the attrib...