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On Multi-Objective Evolutionary Algorithms
[chapter]

2010
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Applied Optimization
*

f

doi:10.1007/978-3-540-92828-7_10
fatcat:i4fbc3y7trfitllfqhgo2ahaka
*m*(x) ≤ f*m*(x * ), ∀*m*∈ {1,... ... ,*M*} and ∃*m*∈ {1,... ...##
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Optimal Control Formulations for the Unit Commitment Problem
[chapter]

2014
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Springer Proceedings in Mathematics & Statistics
*

F j (y j (t)) = a j · (y j (t)) 2 +

doi:10.1007/978-3-319-10046-3_6
fatcat:uuntragogbcxxisgrp34da4bla
*b*j · y j (t) + c j , (1) where a j ,*b*j , c j are the cost coefficients of unit j. ... With these considerations the problem is formulated as the following NLP Minimize x∈R (6T +1)×N J(x) subject to LB ≤ x ≤ UB A eq x =*b*eq A ineq x ≤*b*ineq g(x) = 0 h(x) ≤ 0. ...##
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Model Predictive Control of Vehicle Formations
[chapter]

2009
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Lecture notes in control and information sciences
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→ IR n , and a set U ⊂ IR

doi:10.1007/978-3-540-88063-9_21
fatcat:6e5itzoogjea3jplfgfe656isa
*m*of possible control values. ... By selecting the parameter matrix Λ := ⎡ ⎣ λ 1,0 · · · λ 1,n · · · λ*m*,0 · · · λ*m*,n ⎤ ⎦ , (22) we define the function σ Λ (x) = Λ 1 x , (23) and therefore we define the switching function σ by (20) ...##
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Optimal Formation Switching with Collision Avoidance and Allowing Variable Agent Velocities
[chapter]

2012
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Springer Proceedings in Mathematics & Statistics
*

That is, we want to find a N- tuple

doi:10.1007/978-1-4614-3906-6_11
fatcat:iuzuap7v2ng45f2oukpk2vd4iq
*B*= [*b*i ] N i=1 of different elements of F, such that at some time T > 0, Q(T ) =*B*and all*b*i ∈ F, with*b*i =*b*k . There are*M*N · N! ... Suppose a set of*M*(with*M*≥ N) final positions in R d is specified as F = { f 1 , f 2 , . . . , f*M*}. The problem is to find an assignment between the N agents and N final positions in F. ... It starts by checking the collision condition, given by equation (1) , for the allocation pair i −→ j traveling at velocity v i and k −→*B*j traveling at velocity v k , where*B*j is the optimal target ...##
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A Biased Random Key Genetic Algorithm Approach for Unit Commitment Problem
[chapter]

2011
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Lecture Notes in Computer Science
*

F j (Y th, j ) = a j · (Y th t, j ) 2 +

doi:10.1007/978-3-642-20662-7_28
fatcat:3rlejsva2jdupezg6tntbmawra
*b*j ·Y th t, j + c j , (1) where a j ,*b*j , c j are the cost coefficients of unit j. ...##
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Poster city logistics

2014
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Proceedings of the 18th International Database Engineering & Applications Symposium on - IDEAS '14
*

This research aims to help in establishing new legislative directives by testing their impact both on the company profits and on the life of city residents. A case study is developed and conducted in collaboration with the city hall and with eight companies (four freight transport companies and four retailer companies). The impacts are computed by simulating the companies operation under the new legislation and the new routes are used to analyze the impacts on the city traffic, noise, and congestion.

doi:10.1145/2628194.2628198
dblp:conf/ideas/BessaF14
fatcat:qpqg5vyepng5plm2znpykkx7se
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A Stochastic Dynamic Programming Model for Valuing a Eucalyptus Investment
[chapter]

2008
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Springer Optimization and Its Applications
*

The average growth curve for the amount of wood in a hectare of eucalyptus forest land in each of the regions can be observed in Appendix

doi:10.1007/978-0-387-75181-8_16
fatcat:djvuxym3czb3pbfupel3hdci4a
*B*. ... experiments have been performed using three regions in continental Portugal: 1 -north central coast, 2-central coast, and 3 -river Tejo valley, which present different productivity, as shown in Appendix*B*. ... 8645 3 50288 32013 41219 27033 28473 17896 4 36748 51148 30550 42949 19540 27830 5 48278 46431 39600 39093 27306 25178 Average 37324 35440 30899 29871 20402 19712 Appendix*B*...##
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A Hybrid Genetic Algorithm for Constrained Combinatorial Problems: An Application to Promotion Planning Problems
[chapter]

2011
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Operations Research Proceedings
*

Maximize ∑ N

doi:10.1007/978-3-642-20009-0_48
dblp:conf/or/PereiraFF10
fatcat:hjnldegqczdybla3ctgncrvo6y
*B*i=1 ∑ N S j=1 c i j x i j Subject to: ∑ N S j=1 d j x i j ≤*B*i ∀ 1 ≤ i ≤ N*B*, ∑ N S j=1 d j x i j ≥*b*i ∀ 1 ≤ i ≤ N*B*, ∑ N*B*i=1 c i j x i j ≥ C j ∀ 1 ≤ j ≤ N S , x i j ∈ {0, 1} ∀ 1 ≤ ... Problem size is represented as (a,*b*), where a is the number of breaks and*b*the number of spots. ...##
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Concave minimum cost network flow problems solved with a colony of ants

2012
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Journal of Heuristics
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In matrix (

doi:10.1007/s10732-012-9214-6
fatcat:i3ohsxfgcfguneaifjwmsvy23i
*B*) in Fig. 1 , all pheromone values smaller than τ min or larger than τ max are signalled in bold*font*. ... Here,*M*is a positive large number (say*M*≥ j∈N \{t} d j ). Constraints (4) and (5) refer to the nonnegative and binary nature of the decision variables. ...##
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A Genetic Algorithm Approach for the TV Self-Promotion Assignment Problem

2009
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AIP Conference Proceedings
*

Maximize ∑ N

doi:10.1063/1.3241343
fatcat:zp4rdjrkmng6heuqw2akjd2xae
*B*i=1 ∑ N S j=1 c i j x i j Subject to: ∑ N S j=1 d j x i j ≤*B*i ∀ 1 ≤ i ≤ N*B*, ∑ N S j=1 d j x i j ≥*b*i ∀ 1 ≤ i ≤ N*B*, ∑ N*B*i=1 c i j x i j ≥ C j ∀ 1 ≤ j ≤ N S , x i j ∈ {0, 1} ∀ 1 ≤ ... Problem size is represented as (a,*b*) , where a is the number of breaks and*b*the number of spots. ...##
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Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

2022
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Sustainability
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, which consists of the solutions with wT > wT

doi:10.3390/su14106264
fatcat:dgxc7hif5fdojh2ostiqcpd4oe
*m*and E ≤ E*m*;*B*3 , which consists of the solutions with wT ≤ wT*m*and E ≤ E*m*; and*B*4 , which consists of the solutions with wT > wT*m*and E > E*m*. ... Let set*B*consist of the solutions in the top half, and let wT*m*and E*m*be, respectively, the median values of wT and E of the solutions in set*B*. ...##
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Optimal Hop-Constrained Trees for Nonlinear Cost Flow Networks

2010
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INFOR. Information systems and operational research
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≤R, a ij r 2 +

doi:10.3138/infor.48.1.013
fatcat:xhqth4mm2nbibjc3umnrym3bfy
*b*ij r + c ij + k otherwise, where a ij = 0 for G1 and G2, k =*b*ij for G1, and k = −*b*ij for G2 and G3. ... Let G = (W, A) denote a directed network with a set W of n + 1 vertices (the source vertex and n demand vertices) and with a set A of*m*directed arcs. ...##
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The hop-constrained minimum cost flow spanning tree problem with nonlinear costs: an ant colony optimization approach

2014
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Optimization Letters
*

The cost function used in [7] is the −a ij · x 2 ij +

doi:10.1007/s11590-014-0762-6
fatcat:nhvxluzyqjcvdcxgttrzxsbxqe
*b*ij · x ij , while [10] use −a ij ·x 2 ij +*b*ij ·x ij +c ij , and [5] define the cost function as −a ij ·x α ij +*b*ij ·x ij +c ij with α in ... Nonetheless,*Fontes*[9] provides optimal solution results for cost functions of type F3 and problems with up to 19 nodes. ...##
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A Decision Support System to Analyze the Influence of Distributed Generation in Energy Distribution Networks
[chapter]

2009
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Energy Systems
*

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The Maximum Edge Weight Clique Problem: Formulations and Solution Approaches
[chapter]

2017
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Optimization Methods and Applications
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Acknowledgments This work was carried out, while the second author was a visiting scholar at Texas A&

doi:10.1007/978-3-319-68640-0_10
fatcat:hlkp2u5bvjee3nmcni4mr4c63u
*M*University, College Station, TX, USA, and is partially supported by scholarship SFRH/BSAB/113662/2015 ... Maximize P n 1 iD1 P n jDiC1 w ij y ij subject to y ij C y ik y jk Ä 1; i; j; k 2 V W i < j < k P j;j>i y ij C P j;j<i y ji Ä*b*1; i 2 V y ij C y jl C y lm y il y jm Ä 1; i; j; l;*m*2 V W i < j < l <*m*... Finding a solution to this problem is equivalent to finding a clique of*b*vertices with maximum weight in an edge-weighted complete graph if edge weights are given by*M*d e , where*M*is a strict upper ...
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