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前言

PREFACE

隨著客戶需求的不斷提高，多項(xiàng)目調(diào)度往往處于不確定環(huán)境下，導(dǎo)致實(shí)際調(diào)度方案不能完全按照基準(zhǔn)調(diào)度方案執(zhí)行或需重新安排調(diào)度計(jì)劃。不確定環(huán)境下的多項(xiàng)目調(diào)度問(wèn)題需要充分考慮調(diào)度環(huán)境中的不確定性因素，如天氣原因造成的工期延誤或設(shè)備故障造成的停工等，而這種不確定往往是不可避免且無(wú)法預(yù)測(cè)的。因此，不確定環(huán)境下的多項(xiàng)目調(diào)度問(wèn)題的研究有重要的理論價(jià)值與實(shí)際意義。針對(duì)多項(xiàng)目調(diào)度問(wèn)題中各類不確定因素?cái)_動(dòng)初始調(diào)度計(jì)劃等問(wèn)題展開(kāi)研究，可恢復(fù)或避免擾動(dòng)對(duì)多項(xiàng)目調(diào)度計(jì)劃的影響，以確保多項(xiàng)目順利完工。

項(xiàng)目執(zhí)行過(guò)程中存在諸多不確定性，對(duì)于多項(xiàng)目調(diào)度而言，由于任務(wù)數(shù)量龐大，涉及跨組織的資源調(diào)度，故而不確定環(huán)境下的多項(xiàng)目調(diào)度問(wèn)題具有復(fù)雜性和不確定性等特征，增加了調(diào)度計(jì)劃的制訂難度，從而為多項(xiàng)目調(diào)度的管理帶來(lái)了困難和挑戰(zhàn)。因此，針對(duì)不確定環(huán)境下的多項(xiàng)目調(diào)度問(wèn)題，如何在基準(zhǔn)調(diào)度計(jì)劃制訂階段考慮調(diào)度過(guò)程中存在的不確定因素，合理優(yōu)化項(xiàng)目結(jié)構(gòu)，制訂符合客戶動(dòng)態(tài)需求的調(diào)度方案，已成為項(xiàng)目調(diào)度領(lǐng)域的研究熱點(diǎn)和前沿課題。

作者長(zhǎng)期從事項(xiàng)目調(diào)度和網(wǎng)絡(luò)優(yōu)化等課題的研究，跟蹤國(guó)內(nèi)外的研究動(dòng)態(tài)，本書(shū)是作者多年研究的總結(jié)，同時(shí)也吸取了國(guó)內(nèi)外的最新研究成果。本書(shū)以不確定環(huán)境下的多項(xiàng)目調(diào)度優(yōu)化問(wèn)題為研究對(duì)象，探索動(dòng)態(tài)客戶需求與項(xiàng)目任務(wù)調(diào)度的最佳配置方式。為此，搭建多項(xiàng)目動(dòng)態(tài)調(diào)度的研究框架，構(gòu)建多項(xiàng)目動(dòng)態(tài)調(diào)度優(yōu)化模型，從系統(tǒng)和全局視角研究不確定環(huán)境下的多項(xiàng)目動(dòng)態(tài)調(diào)度優(yōu)化問(wèn)題，豐富了多項(xiàng)目調(diào)度的研究方法，以期為不確定環(huán)境下的多項(xiàng)目動(dòng)態(tài)調(diào)度問(wèn)題提供理論與方法上的指導(dǎo)。

全書(shū)共7章。第1章介紹了不確定環(huán)境下多項(xiàng)目動(dòng)態(tài)調(diào)度優(yōu)化問(wèn)題理論與方法研究的背景和基本研究?jī)?nèi)容。第2章主要分析不確定環(huán)境下多項(xiàng)目調(diào)度的基本屬性及國(guó)內(nèi)外研究現(xiàn)狀。第3章針對(duì)不確定環(huán)境下多項(xiàng)目調(diào)度的工期不確定問(wèn)題展開(kāi)研究，構(gòu)建不確定環(huán)境下的多項(xiàng)目調(diào)度工期-魯棒性均衡優(yōu)化模型，鑒于問(wèn)題的復(fù)雜性，設(shè)計(jì)多級(jí)遺傳算法求解此問(wèn)題。第4章深入分析不確定因素對(duì)多項(xiàng)目調(diào)度內(nèi)部資源使用率的影響，按照活動(dòng)的可執(zhí)行性將其拆分為若干子活動(dòng)，并執(zhí)行非搶占式執(zhí)行模式，在提高多項(xiàng)目調(diào)度資源利用率的基礎(chǔ)上，降低不確定因素對(duì)多項(xiàng)目調(diào)度系統(tǒng)的影響。以工期-成本-質(zhì)量-魯棒性為優(yōu)化目標(biāo)，利用效用函數(shù)建立多目標(biāo)均衡優(yōu)化模型，并設(shè)計(jì)云遺傳算法對(duì)問(wèn)題進(jìn)行求解。第5章闡釋了不確定因素對(duì)工期、客戶滿意度、成本和資源可用量的影響，構(gòu)建面向多干擾的多項(xiàng)目調(diào)度模型，并設(shè)計(jì)雙種群遺傳算法求解問(wèn)題模型。第6章介紹了多項(xiàng)目前攝性調(diào)度問(wèn)題，并建立不確定環(huán)境下多項(xiàng)目前攝性調(diào)度模型，結(jié)合模型的特點(diǎn)設(shè)計(jì)遺傳模擬退火算法求解此問(wèn)題。第7章介紹了多項(xiàng)目調(diào)度的未來(lái)發(fā)展趨勢(shì)。

本書(shū)的撰寫(xiě)得到了教育部人文社科項(xiàng)目資助（15XJC630007、14YJC630038），重慶市教委科學(xué)技術(shù)研究項(xiàng)目資助（KJ1500702）、重慶市社會(huì)科學(xué)規(guī)劃博士項(xiàng)目資助（2016BS080）、博士后科學(xué)基金資助（2017M612951）、重慶市基礎(chǔ)與前沿研究項(xiàng)目資助（cstc2016jcyjA0160）、重慶市教委人文社會(huì)科學(xué)研究項(xiàng)目（17SKG073）、四川外國(guó)語(yǔ)大學(xué)學(xué)術(shù)專著后期資助（sisu201785）。同時(shí)，本書(shū)還得到四川外國(guó)語(yǔ)大學(xué)國(guó)際商學(xué)院物流管理專業(yè)各位同仁的幫助與大力支持。在本書(shū)出版之際，向他們表示真誠(chéng)的感謝。

本書(shū)在創(chuàng)作過(guò)程中借鑒了許多專家的觀點(diǎn)，并參考了大量的文獻(xiàn)資料，雖力圖詳盡列出相關(guān)資料的來(lái)源，但難免有疏忽之處，還請(qǐng)讀者海涵。書(shū)中也有不少創(chuàng)新之處，但作者的某些看法可能還不成熟，可能會(huì)存在考慮不周之處，加之作者能力所限，還望各位專家給予批評(píng)指正。

王偉鑫

2018年5月

CONTENTS

1 概述································································································· 001

1.1 研究背景····································································· 001

1.2 研究意義····································································· 002

1.3 不確定環(huán)境下多項(xiàng)目調(diào)度屬性分析······································ 003

1.3.1 不確定環(huán)境下多項(xiàng)目調(diào)度資源屬性分析·························· 003

1.3.2 不確定環(huán)境下多項(xiàng)目調(diào)度環(huán)境分析······························· 004

2 不確定環(huán)境下多項(xiàng)目調(diào)度問(wèn)題研究綜述··················································· 006

3 工期不確定的多項(xiàng)目調(diào)度研究································································ 011

3.1 問(wèn)題描述····································································· 011

3.2 模型變量及參數(shù)···························································· 012

3.3 工期不確定的多項(xiàng)目調(diào)度魯棒性-工期優(yōu)化分析······················· 013

3.4 建立魯棒性-工期均衡優(yōu)化模型·········································· 015

3.5 求解算法研究······························································· 016

3.5.1 多級(jí)遺傳算法介紹··················································· 016

3.5.2 多級(jí)遺傳算法設(shè)計(jì)··················································· 017

3.5.3 修復(fù)運(yùn)算子··························································· 020

3.5.4 適應(yīng)度計(jì)算··························································· 021

3.5.5 種群規(guī)模和停止運(yùn)算準(zhǔn)則··········································· 021

3.6 仿真試驗(yàn)····································································· 022

3.6.1 算例分析······························································ 022

3.6.2 結(jié)果分析······························································ 027

3.7 本章小結(jié)····································································· 028

4 活動(dòng)不確定的多項(xiàng)目調(diào)度研究································································ 029

4.1 問(wèn)題描述····································································· 029

4.2 示例·········································································· 030

4.3 模型變量及相關(guān)概念······················································· 032

4.3.1 模型變量······························································ 032

4.3.2 相關(guān)概念······························································ 034

4.4 活動(dòng)不確定的多項(xiàng)目調(diào)度模型··········································· 035

4.5 求解算法研究······························································· 037

4.5.1 基于優(yōu)先權(quán)規(guī)則的非搶占式多項(xiàng)目調(diào)度算法···················· 037

4.5.2 云遺傳算法··························································· 039

4.6 仿真試驗(yàn)····································································· 041

4.6.1 算例分析······························································ 041

4.6.2 非搶占式與搶占式操作模式對(duì)比分析····························· 043

4.6.3 算法對(duì)比分析························································· 044

4.6.4 結(jié)果分析······························································ 046

4.7 本章小結(jié)····································································· 047

5 面向多干擾的多項(xiàng)目調(diào)度研究································································ 048

5.1 問(wèn)題描述····································································· 048

5.2 擾動(dòng)恢復(fù)策略······························································· 050

5.3 模型變量及假設(shè)···························································· 051

5.4 多項(xiàng)目調(diào)度的擾動(dòng)分析···················································· 053

5.4.1 多項(xiàng)目調(diào)度的擾動(dòng)因素分析········································ 054

5.4.2 擾動(dòng)的度量··························································· 055

5.5 面向多干擾的多項(xiàng)目調(diào)度模型··········································· 058

5.6 設(shè)計(jì)雙種群遺傳算法······················································· 060

5.7 仿真試驗(yàn)····································································· 065

5.8 本章小結(jié)····································································· 070

6 不確定環(huán)境下的多項(xiàng)目前攝性調(diào)度研究··················································· 071

6.1 問(wèn)題描述····································································· 071

6.2 模型變量及參數(shù)···························································· 073

6.3 前攝性調(diào)度優(yōu)化目標(biāo)分析················································· 075

6.4 多項(xiàng)目前攝性調(diào)度模型···················································· 076

6.5 遺傳模擬退火算法設(shè)計(jì)···················································· 077

6.6 仿真試驗(yàn)····································································· 080

6.7 本章小結(jié)····································································· 083

7 多項(xiàng)目動(dòng)態(tài)調(diào)度的未來(lái)發(fā)展趨勢(shì)····························································· 084

7.1 大數(shù)據(jù)驅(qū)動(dòng)的多項(xiàng)目調(diào)度特征分析······································ 084

7.2 大數(shù)據(jù)驅(qū)動(dòng)的多項(xiàng)目調(diào)度跨組織資源共享模式分析·················· 085

參考文獻(xiàn)·································································································· 088

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