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Solution of Bi-objective Competitive Facility Location Problem Using Parallel Stochastic Search Algorithm

机译：用并行随机搜索算法求解双目标竞争设施选址问题

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Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.

机译：会议记录：第二届可持续超大规模计算系统国际研讨会（NESUS 2015）。克拉科夫（波兰），2015年9月10日至11日。

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Lancinskas Algirdas; Martínez Ortigosa Pilar; Zilinskas Julius;
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年度 2015
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1. Optimizing a bi-objective reliable facility location problem with adapted stochastic measures using tuned-parameter multi-objective algorithms [J] . Jalali Sajjad, Seifbarghy Mehdi, Sadeghi Javad, Knowledge-Based Systems . 2016,第Mara1期

机译：使用调整参数多目标算法，通过调整后的随机措施优化双目标可靠设施选址问题
2. Solving the competitive facility location problem considering the reactions of competitor with a hybrid algorithm including Tabu Search and exact method [J] . Jafar Bagherinejad, Azar Niknam Journal of Industrial Engineering International . 2018,第1期

机译：结合禁忌搜索和精确方法的混合算法，解决考虑竞争者反应的竞争性设施选址问题
3. εdocumentclass[12pt]{minimal}usepackage{amsmath}usepackage{wasysym}usepackage{amsfonts}usepackage{amssymb}usepackage{amsbsy}usepackage{mathrsfs}usepackage{upgreek}setlength{oddsidemargin}{-69pt}egin{document}$$arepsilon $$end{document}-Constraint method for bi-objective competitive facility location problem with uncertain demand scenario [J] . EURO Journal on Computational Optimization . 2020,第1期

机译：ε documentclass [12pt] {minimal} usepackage {ammath} usepackage {kyysym} usepackage {amsfonts} usepackage {amssymb} usepackage {amsbsy} usepackage {mathrsfs} usepackage {supmeek} setLength { oddsidemargin} { - 69pt} begin {document} $$$ varepsilon $$ end {document} -constraint方法对不确定的需求方案的双目标竞争设施位置问题
4. Parallel Shared-Memory Multi-Objective Stochastic Search for Competitive Facility Location [C] . Algirdas Lancinskas, Pilar Martinez Ortigosa, Julius Zilinskas International conference on Euro-Par;International workshop on reproducibility in parallel computing;Workshop on runtime and operating systems for the many - core era;Workshop on software for exascale computing - project workshop;Workshop on techniques and applications for sustainable ultrascale computing systems;Workshop on unconventional high-performance computing;Workshop on high-performance bioinformatics and biomedicine;Workshop on virtualization in high-performance cloud computing;International workshop on multi-/many-core computing systems;Workshop on large-scale distributed virtual environments on clouds and P2P;Workshop on parallel and distributed agent-based simulations;Workshop on on-chip memory hierarchies and interconnects:organization, management andimplementation;Workshop on resiliency in high-performance computing with clouds, grids, and clusters;Workshop on productivity and performance - tools for HPC application development;Workshop on applications of parallel computation in industry and engineering;Workshop on big data management in clouds;Workshop on dependability and interoperable in heterogeneous clouds;Workshop on federative and interoperable cloud infrastructures;International workshop on algorithms, models and tools for parallel computing on heterogeneous platforms . 2014

机译：竞争性设施位置的并行共享内存多目标随机搜索
5. An empirical comparison of tabu search, simulated annealing, and genetic algorithms for facilities location problems. [D] . Arostegui, Marvin Antonio, Jr. 1997

机译：禁忌搜索，模拟退火和遗传算法对设施选址问题的经验比较。
6. Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails [O] . Mansuck Kim, Byung-Jun Yoon 2012

机译：自适应参考更新（ARU）算法。一种有效优化多药鸡尾酒的随机搜索算法
7. Optimizing a bi-objective reliable facility location problem with adapted stochastic measures using tuned-parameter multi-objective algorithms [O] . Sajjad Jalali, Mehdi Seifbarghy, Javad Sadeghi, 2016

机译：使用调谐参数多目标算法进行适应随机措施的双目标可靠设施定位问题

Solution of Bi-objective Competitive Facility Location Problem Using Parallel Stochastic Search Algorithm

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