An Energy-efficient Mathematical Model for the Resource-constrained Project Scheduling Problem: An Evolutionary Algorithm
暂无分享,去创建一个
[1] Pengyu Yan,et al. Energy-efficient bi-objective single-machine scheduling with power-down mechanism , 2017, Comput. Oper. Res..
[2] Lothar Thiele,et al. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.
[3] Makoto Fujishima,et al. A study on energy efficiency improvement for machine tools , 2011 .
[4] Ada Che,et al. Energy-conscious unrelated parallel machine scheduling under time-of-use electricity tariffs , 2017 .
[5] John W. Sutherland,et al. Dynamic scheduling of a flow shop with on-site wind generation for energy cost reduction under real time electricity pricing , 2017 .
[6] George Q. Huang,et al. Hybrid flow shop scheduling considering machine electricity consumption cost , 2013 .
[7] Sanja Petrovic,et al. An investigation into minimising total energy consumption and total weighted tardiness in job shops , 2014 .
[8] Rainer Kolisch,et al. PSPLIB - a project scheduling problem library , 1996 .
[9] Joaquín B. Ordieres Meré,et al. Optimizing the production scheduling of a single machine to minimize total energy consumption costs , 2014 .
[10] John W. Sutherland,et al. A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction , 2011 .
[11] Jason R. Schott. Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization. , 1995 .
[12] Amir Abbas Najafi,et al. A Multi-Objective Imperialist Competitive Algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resource-constrained situations , 2014, Comput. Oper. Res..
[13] Mehmet Bayram Yildirim,et al. A framework to minimise total energy consumption and total tardiness on a single machine , 2008 .
[14] Adriana Giret,et al. Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm , 2013 .
[15] Lothar Thiele,et al. Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study , 1998, PPSN.
[16] Evripidis Bampis,et al. Speed scaling with power down scheduling for agreeable deadlines , 2011, Sustain. Comput. Informatics Syst..
[17] Jian Gao,et al. An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem , 2013 .
[18] A. Isaksson,et al. Scheduling and energy - Industrial challenges and opportunities , 2015, Comput. Chem. Eng..
[19] Shijin Wang,et al. Bi-objective optimization of a single machine batch scheduling problem with energy cost consideration , 2016 .
[20] Chen Fang,et al. An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem , 2012, Comput. Oper. Res..
[21] Min Dai,et al. Energy-efficient dynamic scheduling for a flexible flow shop using an improved particle swarm optimization , 2016, Comput. Ind..
[22] Ling Wang,et al. A knowledge-guided multi-objective fruit fly optimization algorithm for the multi-skill resource constrained project scheduling problem , 2018, Swarm Evol. Comput..
[23] Fayez F. Boctor,et al. An efficient genetic algorithm to solve the resource-constrained project scheduling problem with transfer times: The single mode case , 2018, Eur. J. Oper. Res..
[24] S. Afshin Mansouri,et al. Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption , 2016, Eur. J. Oper. Res..
[25] Cheng Wu,et al. Carbon-efficient scheduling of flow shops by multi-objective optimization , 2016, Eur. J. Oper. Res..
[26] Mostafa Zareei,et al. A multi-objective resource-constrained optimization of time-cost trade-off problems in scheduling project , 2015 .
[27] John W. Sutherland,et al. Scheduling on a single machine under time-of-use electricity tariffs , 2016, Ann. Oper. Res..
[28] Axel Tuma,et al. Energy-efficient scheduling in manufacturing companies: A review and research framework , 2016, Eur. J. Oper. Res..
[29] Guo-Sheng Liu,et al. Minimizing energy consumption and tardiness penalty for fuzzy flow shop scheduling with state-dependent setup time , 2017 .
[30] Quan-Ke Pan,et al. Energy-efficient permutation flow shop scheduling problem using a hybrid multi-objective backtracking search algorithm , 2017 .
[31] Mahdi Bashiri,et al. A NEW APPROACH TO TACTICAL AND STRATEGIC PLANNING IN PRODUCTION– DISTRIBUTION NETWORKS , 2012 .
[32] Gwo-Hshiung Tzeng,et al. Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..
[33] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[34] Mostafa Zandieh,et al. The Effect of Worker Learning on Scheduling Jobs in a Hybrid Flow Shop: A Bi-Objective Approach , 2018 .
[35] Seyed Taghi Akhavan Niaki,et al. A soft-computing Pareto-based meta-heuristic algorithm for a multi-objective multi-server facility location problem , 2013, Appl. Soft Comput..
[36] Jan Karel Lenstra,et al. Scheduling subject to resource constraints: classification and complexity , 1983, Discret. Appl. Math..
[37] Seyed Taghi Akhavan Niaki,et al. A bi-objective aggregate production planning problem with learning effect and machine deterioration: Modeling and solution , 2018, Comput. Oper. Res..
[38] Hadi Mokhtari,et al. An energy-efficient multi-objective optimization for flexible job-shop scheduling problem , 2017, Comput. Chem. Eng..
[39] Tian Bai,et al. An improved fruit fly optimization algorithm for solving traveling salesman problem , 2017, Frontiers of Information Technology & Electronic Engineering.
[40] Lin Li,et al. A multi-level optimization approach for energy-efficient flexible flow shop scheduling , 2016 .
[41] Raymond Chiong,et al. Solving the energy-efficient job shop scheduling problem: a multi-objective genetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption , 2016 .