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In this paper, we have proposed a novel algorithm based on Ant Colony Optimization (ACO) for finding near-optimal solutions for the Multi-dimensional Multi-choice Knapsack Problem (MMKP). MMKP is a discrete optimization problem, which is a variant of the classical 0-1 Knapsack Problem and is also an NP-hard problem. Due to its high computational complexity, exact solutions of MMKP are not suitable...
This paper deals with a problem on edge-colored graphs. The aim is to find a minimum reload cost spanning tree using Ant Colony Optimization (ACO) approach. Given an edge-colored graph, reload costs arise at nodes and depend on the pair of colors on the edges used in traversal through that node. The problem finds practical applications in several domains viz. telecommunication, energy, transportation...
The multi-level lot-sizing (MLLS) problem has been widely studied but still plays an important role in the efficient operation of modern manufacturing and assembly processes. The MLLS problem without restrictive assumption on the product structure is difficult to be solved because it is NP-hard and the situation is even exacerbated by the increasing structure complexity of modern products. Several...
This paper presents a new approach for solving network routing optimization problems. In particular, the goal is to optimize the traffic in the network structured event-driven systems as well as to provide means for efficient adaptation of the system to changes in the environment-i.e. when some nodes and/or links fail. Many network routing optimization problems belong to the class of NP hard problems,...
Traveling salesman problem (TSP) is one of the most famous NP-hard problems, which has wide application background. Ant colony optimization (ACO) is a nature-inspired algorithm and taken as one of the high performance computing methods for TSP. Classical ACO algorithm like ant colony system (ACS) cannot solve TSP very well. The present paper proposes an ACO algorithm with multi-direction searching...
This paper considers an open shop scheduling problem that minimizes bi-objectives, namely makespan and weighted tardiness. This problem, due to its complexity, is ranked in a class of NP-hard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. Thus, we propose an efficient meta-heuristic method by hybridizing a multi-objective simulated annealing...
Anycast communication is a new Internet service defined in IPv6, and it can make a host communication with the one "nearest" member in a group of servers. The anycast routing problem with multiple QoS constrained is known to be NP-complete problem and we can't get satisfying results when using the precise method in polynomial time. In this paper, an improved ant colony optimization algorithm...
To solve a typical NP-hard combinatorial optimization problem-traveling salesman problem, ant colony optimization based on minimum spanning tree(MST-ACO), is presented and the performance is reported. The mechanism of MST-ACO is described from three aspects: adopting dual nearest insertion procedure to initialize the pheromone, integrating reinforcement learning through computing lowbound by 1-minimum...
Heterogeneous multiprocessor systems, assembled with off-the-shelf processors and augmented with reprogrammable devices, thanks to their performance, cost effectiveness and flexibility, have become a standard platform for embedded systems. To fully exploit the computational power offered by these systems, great care should be taken when deciding on which processing element (mapping) and when (scheduling)...
Determining the winners of combinatorial auctions which maximize the profit of the auctioneer is NP-complete problem. This paper presents an efficient approximate searching algorithm IAA for the problem. The new algorithm uses the ant colony optimization algorithm based on heuristic rules, the proposed algorithm not only give the way for identify feasible bids with a given partial solution but also...
Parallel machine problem is a typical scheduling problem with wide applications in practice. As for the scheduling criteria, the total weighted tardiness is always regarded as one of the most important criteria in real situations. The problem of scheduling a given set of independent jobs on unrelated parallel machines to minimize the total weighted tardiness is studied in this paper, which is known...
This paper introduces a new approach for decentralized distributed scheduling in a parallel machine shop environment based on the ant colonies optimization (ACO) algorithm. Distributed scheduling in parallel machine shop environment is a NP hard problem which is important to be studied from both theoretical and practical, point of view. The algorithm developed in this work extends the use of the traveling...
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