FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W316224457> ?p ?o ?g. }

• W316224457 startingPage "113" @default.
• W316224457 abstract "This paper considers a single-machine total weighted completion time scheduling problem with a As the weighted shortest processing time first rule cannot provide an optimal solution, this paper proposes an effective heuristic algorithm to search for a near-optimal solution and compares the performances of both methods with computational experiments. 1. Introduction In traditional machine scheduling problems, job processing times are assumed to be constant for all jobs. However, recent empirical studies in several industries have verified that unit costs decline as firms produce more of a product and gain knowledge or experience. For instance, repeated processing of similar tasks improves worker skills; workers are able to perform setup, to deal with machine operations and software, or to handle raw materials and components at a greater pace (Biskup [1]). This phenomenon is known as the learning effect. Classically, the weighted shortest processing time first (WSPT) rule [8] has been applied to obtain an optimal solution for the total weighted completion time in a single-machine scheduling problem. However, this rule fails to provide an optimal solution when the effect is present. This rule is closely examined and its performance assessed relative to another proposed heuristic algorithm. In previous research concerning scheduling problems on a single machine with considerations, Biskup [1] assumed that a job's processing time is a decreasing function of its position in a sequence, considered two single-machine scheduling problems, and showed that both problems could be solved in polynomial time. Continuing analysis of Biskup's [1] model, Mosheiov [5] pointed out that some problems with a effect are more complex than those in the traditional problem and proposed a counterexample showing that the total weighted completion time problem might not be minimized by the WSPT rule in the context of learning. Lee et al. [4] considered a bi-criterion singlemachine scheduling problem with considerations. In addition, Mosheiov [6] further considered flow time minimization on parallel identical machines. Mosheiov and Sidney [7] extended the setting to allow the in the production process of some jobs to be faster than that of others. Lee and Wu [3] further considered the problem of minimizing total completion time in a two-machine flowshop with a The problem in this study has been mentioned in Mosheiov's work [5] concerning a counterexample, but to my knowledge it has not been further discussed in the literature. The rest of this paper is organized as follows. Background of the scheduling problem is provided and three elimination rules to enhance the efficiency of the search for an optimal solution are proposed in the next section. A heuristic algorithm is proposed in Section 3. Computational results for the performance of the WSPT rule and the proposed heuristic algorithm are presented in Section 4. A conclusion is given in the last section. 2. Background and adjacency properties 3. Heuristic algorithms The WSPT rule schedules jobs in decreasing order of w^sub j^/p^sub j^. This rule is studied with respect to the following proposed algorithm. Heuristic Algorithm (HA): Step 1 : Perform the shortest processing time first (SPT) rule in terms of job processing times, i.e., schedule jobs in decreasing order of p and let S denote the resulting schedule. Set 51 as the initial solution. Step 2: Check adjacent jobs in schedule S from beginning to end: if the condition w^sub j^/p^sub j^ >w^sub j^/p^sub j^ is met, interchange the positions of the two adjacent jobs to create a new sequence. Step 3: Compute the completion time of the new sequence and compare it with the initial solution. If the new one is smaller, replace the initial sequence with the new one. Otherwise, keep the initial one. …" @default.
• W316224457 created "2016-06-24" @default.
• W316224457 creator A5087320585 @default.
• W316224457 date "2006-03-01" @default.
• W316224457 modified "2023-09-24" @default.
• W316224457 title "The Development of a Solution to the Single-Machine Total Weighted Completion Time Problem with a Learning Effect" @default.
• W316224457 hasPublicationYear "2006" @default.
• W316224457 type Work @default.
• W316224457 sameAs 316224457 @default.
• W316224457 citedByCount "0" @default.
• W316224457 crossrefType "journal-article" @default.
• W316224457 hasAuthorship W316224457A5087320585 @default.
• W316224457 hasConcept C10431821 @default.
• W316224457 hasConcept C111919701 @default.
• W316224457 hasConcept C11413529 @default.
• W316224457 hasConcept C126255220 @default.
• W316224457 hasConcept C13280743 @default.
• W316224457 hasConcept C154945302 @default.
• W316224457 hasConcept C162324750 @default.
• W316224457 hasConcept C173801870 @default.
• W316224457 hasConcept C175444787 @default.
• W316224457 hasConcept C205649164 @default.
• W316224457 hasConcept C206729178 @default.
• W316224457 hasConcept C2777526511 @default.
• W316224457 hasConcept C2780271269 @default.
• W316224457 hasConcept C311688 @default.
• W316224457 hasConcept C33923547 @default.
• W316224457 hasConcept C41008148 @default.
• W316224457 hasConcept C55416958 @default.
• W316224457 hasConcept C68387754 @default.
• W316224457 hasConceptScore W316224457C10431821 @default.
• W316224457 hasConceptScore W316224457C111919701 @default.
• W316224457 hasConceptScore W316224457C11413529 @default.
• W316224457 hasConceptScore W316224457C126255220 @default.
• W316224457 hasConceptScore W316224457C13280743 @default.
• W316224457 hasConceptScore W316224457C154945302 @default.
• W316224457 hasConceptScore W316224457C162324750 @default.
• W316224457 hasConceptScore W316224457C173801870 @default.
• W316224457 hasConceptScore W316224457C175444787 @default.
• W316224457 hasConceptScore W316224457C205649164 @default.
• W316224457 hasConceptScore W316224457C206729178 @default.
• W316224457 hasConceptScore W316224457C2777526511 @default.
• W316224457 hasConceptScore W316224457C2780271269 @default.
• W316224457 hasConceptScore W316224457C311688 @default.
• W316224457 hasConceptScore W316224457C33923547 @default.
• W316224457 hasConceptScore W316224457C41008148 @default.
• W316224457 hasConceptScore W316224457C55416958 @default.
• W316224457 hasConceptScore W316224457C68387754 @default.
• W316224457 hasIssue "1" @default.
• W316224457 hasLocation W3162244571 @default.
• W316224457 hasOpenAccess W316224457 @default.
• W316224457 hasPrimaryLocation W3162244571 @default.
• W316224457 hasRelatedWork W109241435 @default.
• W316224457 hasRelatedWork W1445900351 @default.
• W316224457 hasRelatedWork W1971744510 @default.
• W316224457 hasRelatedWork W1972702953 @default.
• W316224457 hasRelatedWork W2022856911 @default.
• W316224457 hasRelatedWork W2067299508 @default.
• W316224457 hasRelatedWork W2141097584 @default.
• W316224457 hasRelatedWork W2148301389 @default.
• W316224457 hasRelatedWork W2157530413 @default.
• W316224457 hasRelatedWork W2172284129 @default.
• W316224457 hasRelatedWork W2186806673 @default.
• W316224457 hasRelatedWork W2335223640 @default.
• W316224457 hasRelatedWork W2356341257 @default.
• W316224457 hasRelatedWork W2568675888 @default.
• W316224457 hasRelatedWork W2751180135 @default.
• W316224457 hasRelatedWork W2785847890 @default.
• W316224457 hasRelatedWork W3026666604 @default.
• W316224457 hasRelatedWork W3205966826 @default.
• W316224457 hasRelatedWork W38423048 @default.
• W316224457 hasRelatedWork W2181480523 @default.
• W316224457 hasVolume "23" @default.
• W316224457 isParatext "false" @default.
• W316224457 isRetracted "false" @default.
• W316224457 magId "316224457" @default.
• W316224457 workType "article" @default.