具有學(xué)習(xí)效應(yīng)的排序問題的某些新進展

趙 傳 立

(沈陽師范大學(xué) 數(shù)學(xué)與系統(tǒng)科學(xué)學(xué)院, 沈陽 110034)

具有學(xué)習(xí)效應(yīng)的排序問題的某些新進展

趙 傳 立

(沈陽師范大學(xué) 數(shù)學(xué)與系統(tǒng)科學(xué)學(xué)院, 沈陽 110034)

Biskup 首先將學(xué)習(xí)效應(yīng)的的概念引入到排序問題中,并且在2008年給出具有學(xué)習(xí)效應(yīng)的排序問題的全面綜述。從此以后,具有學(xué)習(xí)效應(yīng)的排序問題持續(xù)引起研究者的興趣。除了Biskup綜述所提到的模型外,文獻中還有其他學(xué)習(xí)效應(yīng)模型,對近年來文獻中出現(xiàn)的具有學(xué)習(xí)效應(yīng)的排序模型做一簡要介紹。主要考慮3類模型:工件的實際加工時間依賴于具體的位置函數(shù)的模型,工件的實際加工時間依賴于抽象的位置函數(shù)的模型,工件的實際加工時間依賴于截斷式學(xué)習(xí)函數(shù)的模型。

排序; 學(xué)習(xí)效應(yīng); 單機; 平行機; 流水作業(yè)

作為新型排序的一個組成部分,具有學(xué)習(xí)效應(yīng)的排序問題持續(xù)受到研究者的關(guān)注。在Biskup的綜述之后,近年又出現(xiàn)了許多新模型。這些新模型一部分是利用已有模型加以組合而成,另一部分則是對已有模型做某些推廣。本文僅介紹后一類模型,關(guān)注2009年以后的某些研究進展。主要介紹各個模型中常見目標(biāo)函數(shù)在一般情況下的結(jié)論,關(guān)注多項式最優(yōu)算法,不涉及啟發(fā)式算法、分支定界法等。對于特殊情況和特殊目標(biāo)函數(shù)的有關(guān)結(jié)論不做介紹。

1 主要模型

主要介紹近年來產(chǎn)生的3類新模型:工件的實際加工時間是具體函數(shù)的模型,工件的實際加工時間是抽象函數(shù)的模型,工件的實際加工時間是截斷式學(xué)習(xí)函數(shù)的模型。

1.1工件的實際加工時間是具體函數(shù)的模型

表1 加工時間是具體函數(shù)的模型

續(xù)表1

加 工 時 間 問 題 計算復(fù)雜性或算法參考文獻pAj[r]=pj(αa∑r-1k=1p[k]+β)1pAj[r]，SpsdfSPT[16]α≥0，β≥0，00pAj[r]=pj(αa∑r-1k=1lnp[k]+β)1pAj[r]fSPT[21]α≥0，β≥0，0

1.2工件的實際加工時間是抽象函數(shù)的模型

表2 加工時間是抽象函數(shù)的模型

續(xù)表2

加 工 時 間 問題計算復(fù)雜性或算法 參考文獻pAj[r]=pjf(∑r-1k=1p[k])g(r)1pAj[r]f，f∈{Cmax，∑Ckj}SPT[36?38]f不增，f′不減，g不增1pAj[r]，Spsdf，f∈{Cmax，∑Cj}SPT1pAj[r]，qpsdf，f∈{Cmax，∑Ckj}SPTpAj[r]=f(j，r)Fmprop，pAj[r]CmaxO(n5)[40?42]PmpAj[r]∑mi=1CiO(nm+2)[41]PmpAj[r]，rej∑ACj+∑RejO(nm+3)[43]PmpAj[r]，rej∑mi=1Cmaxi+∑RejO(nm+3)[43]pAj[r]=pjf(∑r-1k=1pA[k]∑nk=1pk)g(r)1pAj[r]，Spsdf，f∈{Cmax，∑Cj}SPT[44]f不增，f′不減，g不增pAj[r]=pjf(∑r-1k=1βkp[k])g(r)1pAj[r]f，f∈{Cmax，∑Ckj}SPT[45]f不增，f′不減，g不增，0<βj不減pAj[r]=f(pj，r)1pAj[r]，PRMαCmax+β∑Ej+λ∑TjO(n4)[46]pAj[r]=pjf(∑r-1k=1βkp[k]，r)，βj不減1pAj[r]，Spsdf，f∈{Cmax，∑Cj}SPT[47]

1.3工件的實際加工時間是截斷式的模型

表3 截斷式學(xué)習(xí)效應(yīng)模型

續(xù)表3

加 工 時 間 問題計算復(fù)雜性或算法 參考文獻pAj[r]=pjmax{raj，β}，0<β<11pAj[r]，CON∑(αEj+βTj+γd)O(n3)[57]1pAj[r]，SLK∑(αEj+βTj+γdj)1pAj[r]ff∈{Cmax，∑Cj，∑∑Ci-CjpAj[r]=pjmax{(1-∑r-1k=1p[k]∑nk=1p[k])a，β}1pAj[r]f，f∈{Cmax，∑Cj}SPT[58]a>1，0<β<1pAj[r]=pjmax{(aα-∑r-1k=1p[k]∑nk=1pk+b)，β}1pAj[r]f，f∈{Cmax，∑Ckj}SPT[60]a≥0，b≥0，a+b=1，a≥1，0<β<1

2 結(jié) 論

關(guān)于具有學(xué)習(xí)效應(yīng)的排序問題還有許多結(jié)論,限于本文涉及內(nèi)容和資料的局限,不可能完全提及。即使對于提到的模型的結(jié)論也難免掛一漏萬,因此文中內(nèi)容僅供感興趣的讀者參考。從上節(jié)所提各個模型的研究成果來看,對于工件的實際加工時間是具體函數(shù)的模型,雖模型較多,但研究結(jié)論主要集中在單機問題。具有一般性結(jié)論的目標(biāo)函數(shù)主要是最大完工時間和完工時間和,且所用方法是常見的SPT規(guī)則。對于工件的實際加工時間是抽象函數(shù)的模型,某些模型的研究結(jié)果還相對較少,有些主要集中在某一具體機器環(huán)境的特定目標(biāo)函數(shù)。對于截斷式學(xué)習(xí)效應(yīng)的排序模型,由于提出的時間相對較短,目前研究成果相對較少。在未來的工作中,對于各個模型可以考慮如下研究方向:對于實際加工時間是具體函數(shù)的模型,針對具體模型的機器環(huán)境是平行機還是車間作業(yè),研究目標(biāo)函數(shù)范圍更廣泛的問題;對于工件的實際加工時間是抽象函數(shù)的模型,可研究包括多個具體函數(shù)的抽象函數(shù)模型,使其結(jié)論具有一般性;對于截斷式學(xué)習(xí)效應(yīng)的排序模型,根據(jù)不同的加工時間函數(shù),考慮其他形式的階段學(xué)習(xí)效應(yīng)模型。

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Recentadvanceinschedulingwithlearningeffects

ZHAOChuanli

(School of Mathematics and Systems Science, Shenyang Normal University, Shenyang 110034, China)

The concept of a learning effect on scheduling problems was first introduced by Biskup. The comprehensive survey paper on scheduling problems with learning effects was conducted by Biskup in 2008. Since then there has been an increasing interest in scheduling problems with learning effects. Therefore, besides the scheduling models mentioned in the survey of Biskup, there are several other new learning effect scheduling models in the literature. The goal of this paper was to provide a briefly review of the literature on the scheduling problems with learning effects in recent years. We mainly consider three models: 1) the actual processing time of jobs depend on specific position function; 2) the actual processing time of jobs depend on abstract position function; 3) the actual processing time of jobs depend on a truncated learning functions.

scheduling; learning effects; single machine; parallel machine; flow shop

2014-09-01。

遼寧省教育廳科學(xué)技術(shù)研究項目(L2014433)。

趙傳立(1958-),男,黑龍江泰來人,沈陽師范大學(xué)教授,博士,碩士研究生導(dǎo)師。

1673-5862(2014)04-0453-08

O223

: A

10.3969/ j.issn.1673-5862.2014.04.001