Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation | Zendy

Li Sun | Zendy; Bin Wu | Zendy; Lei Ning | Zendy

Open Access

Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation

Author(s) -

Li Sun,

Bin Wu,

Lei Ning

Publication year - 2021

Publication title -

shock and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.418

H-Index - 45

eISSN - 1875-9203

pISSN - 1070-9622

DOI - 10.1155/2021/6687525

Subject(s) - learning effect , single machine scheduling , absolute deviation , computer science , scheduling (production processes) , resource allocation , mathematical optimization , due date , job shop scheduling , mathematics , statistics , schedule , economics , computer network , microeconomics , operating system

We investigate parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times, DeJong’s learning effect, rate-modifying activity, and resource allocation. Each machine has a rate-modifying activity. We consider two versions of the problem to minimize the sum of the total completion times, the total absolute deviation of job completion times, and the total resource allocation and the sum of the total waiting times, the total absolute deviation of job waiting times, and the total resource allocation, respectively. The problems under our present model can be solved in polynomial time.

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