{"id":14160,"date":"2025-12-11T08:05:25","date_gmt":"2025-12-11T07:05:25","guid":{"rendered":"https:\/\/www.ibisc.univ-evry.fr\/xiechen-zhang-will-defend-his-doctoral-thesis-on-friday-december-12-2025-multi-criteria-and-stochastic-optimization-for-scheduling\/"},"modified":"2025-12-22T16:50:17","modified_gmt":"2025-12-22T15:50:17","slug":"xiechen-zhang-will-defend-his-doctoral-thesis-on-friday-december-12-2025-multi-criteria-and-stochastic-optimization-for-scheduling","status":"publish","type":"post","link":"https:\/\/www.ibisc.univ-evry.fr\/en\/xiechen-zhang-will-defend-his-doctoral-thesis-on-friday-december-12-2025-multi-criteria-and-stochastic-optimization-for-scheduling\/","title":{"rendered":"Xiechen ZHANG will defend his doctoral thesis on Friday, December 12, 2025: \u201cMulti-criteria and stochastic optimization for scheduling\u201d"},"content":{"rendered":"
\n\t\t\t\t\t
\n\t\t\t\t\t\t

Xiechen ZHANG defends his doctoral thesis on Friday December 12th, 2025 at 2 pm, room 334 of the IBGBI building, \u00c9vry Paris-Saclay University.<\/p>\n

Title: Multi-criteria and stochastic optimization for scheduling problems<\/h2>\n

Abstract<\/strong>:<\/h2>\n
\n
\n
\n
\n
\n
Multi-criteria scheduling under uncertainty has attracted increasing interest from academics and practitioners due to its diverse applications,<\/div>\n
such as cloud computing, industrial production, and energy efficiency. However, this area remains relatively underexplored in theoretical<\/div>\n
computer science. The coexistence of uncertainties and conflicting criteria poses fundamental challenges: how can we ensure the robustness<\/div>\n
of solutions while guaranteeing their quality within reasonable computational times? This thesis studies three new bi-criteria stochastic scheduling<\/div>\n
problems, focusing particularly on multi-scenario settings and parameters that contain only partial probabilistic information.<\/div>\n
\u00a0<\/div>\n
First, we study a novel multi-scenario bi-criteria identical parallel machine scheduling problem, where job processing times are polynomial functions<\/div>\n
of a continuous scenario parameter. The criteria to simultaneously optimize are the total completion time and the makespan. We analyze the complexity of the<\/div>\n
monocriterion cases, propose an exact polynomial-time algorithm for minimizing total completion time, and design an approximation algorithm<\/div>\n
with a provable performance guarantee for makespan minimization. For the bi-criteria case, we provide a 2-approximation algorithm for any<\/div>\n
number of machines and an (1 + \u03f5)- approximation algorithm when the number of machines is fixed to find approximate sets for the possible<\/div>\n
Pareto set.<\/div>\n
\u00a0<\/div>\n
Second, to address the potential low robustness of the possible Pareto set, which may perform well in a few scenarios but poorly<\/div>\n
in most, we investigate the computation of the multi-scenario efficient set, an extension of the efficient frontier for multi-criteria problems under<\/div>\n
uncertainty. For a refined version of the above problem, we develop an iterative dynamic programming algorithm with an improved pruning<\/div>\n
technique and prove that it yields an FPTAS when the number of machines is constant.<\/div>\n
\u00a0<\/div>\n
Finally, motivated by practical concerns of sustainability, we study stochastic bi-criteria unrelated parallel machine scheduling under time-of-use<\/div>\n
(ToU) electricity pricing, where only partial probability information is available for uncertain job processing times. For the problem, we formulate<\/div>\n
a chance-constrained bicriteria model, transform it into deterministic models, and reinforce them with valid inequalities. Furthermore, we design<\/div>\n
approximation algorithms to compute a (1 + \u03f5)-approximate Pareto set and develop a clustering technique for instances with many time intervals,<\/div>\n
effectively reducing their number while preserving near-optimality.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>

Composition of the doctoral thesis jury<\/span><\/h3>\n<\/div>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n
Jury member<\/th>\nTitle<\/th>\nPlace of work<\/th>\nRole in the jury<\/th>\n<\/tr>\n<\/thead>\n
\u00c9ric ANGEL<\/td>\nFull Professor<\/td>\nUniversity of \u00c9vry Paris-Saclay<\/td>\nThesis supervisor<\/td>\n<\/tr>\n
Christian ARTIGUE<\/td>\nCNRS Research Director<\/td>\nLAAS, University of Toulouse<\/td>\nReviewer<\/td>\n<\/tr>\n
Cristina BAZGAN, LAMSADE<\/td>\nFull Professor<\/td>\nParis Dauphine University<\/td>\nExaminer<\/td>\n<\/tr>\n
Feng CHU<\/td>\nFull Professor<\/td>\nUniversity of \u00c9vry Paris-Saclay<\/td>\nCo-supervisor<\/td>\n<\/tr>\n
Johanne COHEN<\/td>\nCNRS Research Director<\/td>\nLISN, Paris-Saclay University<\/td>\nExaminer<\/td>\n<\/tr>\n
Chistophe D\u00dcRR<\/td>\nCNRS Research Director<\/td>\nLIP6, Sorbonne University<\/td>\nExaminer<\/td>\n<\/tr>\n
Imed KACEM, LCOMS<\/td>\nFull Professor<\/td>\nUniversity of Lorraine<\/td>\nReviewer<\/td>\n<\/tr>\n
Damien REGNAULT<\/td>\nSenior Lecturer HDR<\/td>\nUniversity of \u00c9vry Paris-Saclay, LISN<\/td>\nCo-supervisor<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
<\/div>
<\/div>
    \n
  • Date: Friday, December 12, 2025, 2 p.m.<\/li>\n
  • Location: Room 334 of the IBGBI building, \u00c9vry Paris-Saclay University<\/strong>.<\/li>\n
  • Doctoral student: Xiechen ZHANG, Universit\u00e9 \u00c9vry Paris-Saclay, IBISC AROBAS team<\/li>\n
  • Thesis supervisors: Eric ANGEL (Professor, University of \u00c9vry, IBISC AROBAS team), Thesis supervisor; Feng CHU (Professor, University of \u00c9vry, IBISC AROBAS team), Thesis co-supervisor; Damien REGNAULT (Senior Lecturer, University of \u00c9vry, IBISC AROBAS team), Thesis co-supervisor<\/li>\n<\/ul>\n<\/div>
    <\/div>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":12,"featured_media":1364,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[41,41,53,53,162,9,52,52,169,169],"tags":[],"class_list":{"0":"post-14160","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-in-the-headlines","9":"category-arobas-team","11":"category-events","12":"category-uncategorized","13":"category-research","15":"category-phd-thesis-defense"},"acf":[],"_links":{"self":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/posts\/14160"}],"collection":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/comments?post=14160"}],"version-history":[{"count":7,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/posts\/14160\/revisions"}],"predecessor-version":[{"id":14167,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/posts\/14160\/revisions\/14167"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/media\/1364"}],"wp:attachment":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/media?parent=14160"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/categories?post=14160"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/tags?post=14160"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}