Coordination of multi agent systems remains as a problem since there is no prominent method to completely solve this problem. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisation problems with metaheuristic algorithms. The idea borrowed from swarm intelligence seems working much better than those implementations suggested...

The Multiple-Choice Multi-Dimension Knapsack Problem (MMKP) is a variant of the 0-1 knapsack problem, an NP-Hard problem. Due to its high computational complexity, algorithms for exact solution of the MMKPs are not suitable for most real-time decision-making applications, such as quality adaptation and admission control for interactive multimedia systems, or service level agreement (SLA) manage...

Problem Definition This problem deals with packing a maximum reward set of items into a knapsack of given capacity, when the item-sizes are random. The input is a collection of n items, where each item i ∈ [n] := {1, · · · , n} has reward r i ≥ 0 and size S i ≥ 0, and a knapsack capacity B ≥ 0. In the stochastic knapsack problem, all rewards are deterministic but the sizes are random. The rando...

This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding stru...

Ant colony optimization is a metaheuristic that mainly used for solving hard combinatorial problems. The distinctive feature of ant learning mechanism based on from positive examples. This also the case in other learning-based metaheuristics such as evolutionary algorithms and particle swarm optimization. Examples nature, however, indicate negative learning—in addition to learning—can beneficia...

In this paper, we present a practical case of the multiobjective knapsack problem which concerns the elaboration of the optimal action plan in the social and medico-social sector. We provide a description and a formal model of the problem as well as some preliminary computational results. We perform an empirical analysis of the behavior of three metaheuristic approaches: a fast and elitist mult...

This paper looks at a Multi-Period Renewal equipment problem (MPR). It is inspired by a specific real-life situation where a set of hardware items is to be managed and their replacement dates determined, given a budget over a time horizon comprising a set of periods. The particular characteristic of this problem is the possibility of carrying forward any unused budget from one period to the nex...

The Genetic Immune Strategy for Multiple Objective Optimization (GISMOO) is a hybrid algorithm for solving multiobjective problems. The performance of this approach has been assessed using a classical combinatorial multiobjective optimization benchmark: the multiobjective 0/1 knapsack problem (MOKP) [1] and two-dimensional unconstrained multiobjective problems (ZDT) [2]. This paper shows that t...