Online Scheduling on Two Uniform Unbounded Parallel-Batch Machines to Minimize Makespan

We study an online(over time)scheduling problem on two uniform unbounded parallel-batch machines with processing speed 1 and v(0<≤1),respectively,to minimize the makespan.We first show that no online algorithm can have a competitive ratio less than 1+αL,whereαL=(√5−1)/2≈0.618 if 0≤1/2,andαL=α2(v)is the positive root ofα^(3)+3α^(2)+(3−1/v)α−1/v=0 if1/2≤1.This lower bound is still valid when all jobs have the same processing times.Then,we provide an online algorithm with a competitive ratio at most min{(√5+1)/2,√2/v}.When the jobs have the same processing times,we present the best possible online algorithm with a competitive ratio 1+αL.

Online Scheduling with Unit Processing Times and Processing Set Restrictions

This paper investigates online scheduling problems with processing set restrictions.There is a sequence of jobs that are revealed one by one over list,where each job has unit processing time.A job can only be processed by a subset of the machines,namely the processing set of the job.The objective is to minimize the makespan.For m machines with two different processing sets,we propose an optimal algorithm with a competitive ratio of 3/2.For three machines with inclusive processing sets,an optimal algorithm with competitive ratio 5/3 is provided.

Online Scheduling on a Parallel Batch Machine with Delivery Times and Limited Restarts

The online scheduling on an unbounded parallel batch machine with delivery times and limited restarts is studied in this paper.Here,online means that jobs arrive over time and the characteristics of a job become known until it arrives.Limited restarts mean that once a running batch contains at least one restarted job,it cannot be restarted again.The goal is to minimize the time by which all jobs have been delivered.We consider a restricted model that the delivery time of each job is no more than its processing time.We present a best possible online algorithm with a competitive ratio of 3/2 for the problem.

Online Scheduling on Two Parallel Identical Machines Under a Grade of Service Provision

In this paper,we investigate online scheduling problems on two parallel identical machines under a grade of service provision with makespan as the objective function.The jobs arrive over time and each job can be scheduled only when it has already been arrived.We consider three different versions:(i)the two machines cannot be idle at the same time until all arrived jobs have been processed;(ii)further to the first problem,jobs are processed on a first-come,first-serviced basis;(iii)each job must be assigned to one of the two machines as soon as it arrives.Respectively for three online scheduling problems,optimal online algorithms are proposed with competitive ratio(√5+1)/2,(√5+1)/2 and 5/3.

Optimizing Vaccine Access: A Web-Based Scheduling System with Geo-Tagging Integration and Decision Support for Local Health Centers

The system created aims to produce an online vaccination appointment scheduling system with geo-tagging integration and a decision-support mechanism for neighborhood health clinics. With a decision support mechanism that suggests the essential vaccines based on their account details, it is made to meet the unique vaccination needs of each patient. The system includes immunizations that are accessible locally, and patients and midwives can manage their own corresponding information through personal accounts. Viewers of websites can visualize the distribution of vaccines by purok thanks to geotagging. The Agile Scrum Methodology was modified by the researchers for early delivery, change flexibility, and continual system improvement in order to accomplish the study’s main goal. In order to assess the system’s acceptability in terms of functional adequacy, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability, it was designed in accordance with the ISO 25010 Product Software Quality Standards. Following the assessment, the system was given an average total weighted mean score of 4.62, which represents a verbal interpretation of “strongly agree”. This score demonstrates that the evaluators were in agreement that the system met the requirements of ISO 25010 for Product Software Quality Standards.

Hierarchical On-line Scheduling of Multiproduct Batch Plants with a Combined Approach of Mathematical Programming and Genetic Algorithm

In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.

On-Line Scheduling for Jobs with Arbitrary Release Times on Parallel Related Uniform Machines

A parallel related uniform machine system consists of m machines with different processing speeds. The speed of any machine is independent on jobs. In this paper, we consider online scheduling for jobs with arbitrary release times on the parallel uniform machine system. The jobs appear over list in terms of order. An order includes the processing size and releasing time of a job. For this model, an algorithm with competitive ratio of 12 is addressed in this paper.

Online Over Time Scheduling on Parallel-Batch Machines:A Survey

Online scheduling is a rapidly developed branch in scheduling theory.In this paper,we present an extensive survey for online over time scheduling on parallel-batch machines.Some open problems are proposed for further research.

Integrated schedule of order picking and delivery for instant delivery

In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,which integrates order delivery by depicting order location dispersion in an online order picking strategy.Order delivery,including delivery person assignment and route planning,is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time.A rule-based online order picking strategy is established,and a customized ant colony optimization(ACO)algorithm is proposed to optimize order delivery.Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective.