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By Peter I. Cowling, Peter Merz

This e-book constitutes the refereed court cases of the tenth ecu convention on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2010, held in Instanbul, Turkey, in April 2010. The 24 revised complete papers awarded have been conscientiously reviewed an chosen from sixty nine submissions. The papers current the most recent learn and speak about present advancements and purposes in metaheuristics - a paradigm to successfully remedy tough combinatorial optimization difficulties showing in a number of business, cost-efficient, and clinical domain names. fashionable examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu seek, scatter seek, memetic algorithms, variable local seek, iterated neighborhood seek, grasping radomized adaptive seek tactics, estimation of distribution algorithms and ant colony opitmization

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Due to the fixed transformation, the vectors may lose diversity among them, resulting the population to converge at a sub-optimal point, and A Real-Integer-Discrete-Coded DE Algorithm 39 Table 1. Different cases under the mutation operation to binary variables (α,t) (β,t) (γ,t) Column → xj xj xj Row ↓ (1) (2) (3) (i,t) (4) x ¯j (5) (6) (7) (1) 0 0 0 0 0 0 (2) 0 1 1 0 0 0 (3) 1 0 0 1 1 1 (4) 1 1 1 1 1 1 (5) 0 1 0 F (6) 0 0 1 −F (7) 1 1 (8) 1 0 (0,1) 1 <0 0 0 1+F >1 0 1 1 − F (0,1) 1 0 1 0 1 1 0 1 0 1 0 0 1 0 1 1 0 (8) if if if if if if if if if if if if if if if if (t) r1 (t) r1 (t) r2 (t) r2 (t) r3 (t) r3 (t) r4 (t) r4 (t) r5 (t) r5 (t) r6 (t) r6 (t) r7 (t) r7 (t) r8 (t) r8 pm < pm pm < pm pm < pm pm < pm pm < pm pm < pm pm < pm pm < pm 2.

The first column indicates the names of the instances. Columns LB(p), LB(p + r), AH, HM A present the lower bounds for the strategies based on the classical p-median problem, the (p + r)-median problem [1], the alternating heuristic [5], and the hybrid memetic algorithm, respectively. Note that the HMA lower bound dominates the other ones. Nevertheless, the difference between HMA and LB(p) bounds is small. For the instance 511, these bounds coincide. We may conclude that LB(p) is a good approximation for the leader behavior.

P. ) PPSN 2004. LNCS, vol. 3242, pp. 172–181. Springer, Heidelberg (2004) 25. : Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks. In: Parameter Setting in Evolutionary Algorithms, pp. 121–142. com 2 CEG-IST, Center for Management Studies, Instituto Superior T´ecnico, TagusPark, Av. pt 3 Associate Researcher at LAMSADE, Universit´e Paris-Dauphine, Place De Lattre de Tassigny, 75 775 Paris Cedex 16, France Abstract. The successful application of differential evolution (DE) algorithms to various real-valued problems encourages to develop some integer-coded versions of DE for working directly with integer and discrete variables of a problem.

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