Single-machine scheduling

About: Single-machine scheduling is a research topic. Over the lifetime, 2473 publications have been published within this topic receiving 56288 citations.

An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem

Abstract: This paper focuses on improvements to the Bees Algorithm (BA) with slope angle computation and Hill Climbing Algorithm (SACHCA) during the local search process. First, the SAC was employed to determine the inclination of the current sites. Second, according to the slope angle, the HCA was utilised to guide the algorithm to converge to the local optima. This enabled the global optimum of the given problem to be found faster and more precisely by focusing on finding the available local optima first before turning the attention on the global optimum. The proposed enhancements to the BA have been tested on continuous-type benchmark functions and compared with other optimisation techniques. The results show that the proposed algorithm performed better than other algorithms on most of the benchmark functions. The enhanced BA performs better than the basic BA, in particular on higher dimensional and complex optimisation problems. Finally, the proposed algorithm has been used to solve the single machine scheduling problem and the results show that the proposed SAC and HCA-BA outperformed the basic BA in almost all the considered instances, in particular when the complexity of the problem increases.

A meta-heuristic approach to single machine scheduling problems

Abstract: A new meta-heuristic evolutionary algorithm, named a memetic algorithm, for solving single machine total weighted tardiness scheduling problems is presented in this paper. Scheduling problems are proved to be NP-hard (Non-deterministic polynomial-time hard) types of problems and they are not easily or exactly solved for larger sizes. Therefore, application of the meta-heuristic technique to solve such NP hard problems is pursued by many researchers. The memetic algorithm is a marriage between population-based global searches with local improvement for each individual. The algorithm is tested with benchmark problems available in the OR (operations research) library. The results of the proposed algorithm are compared with the best available results and were found to be nearer to optimal. The memetic algorithm performs better than the heuristics like earliest due date and modified due date.

Minimising the total completion time in a single machine scheduling problem under bimodal flexible periodic availability constraints

Abstract: In many scheduling problems, machines can face availability constraints and as a result, they may stop for a while. In this paper, a novel definition for single machine scheduling problem with flexible periodic availability constraints has been provided. According to this definition, in each period, the duration of unavailability corresponding to the continuous working time of the machine changes in a discrete manner and it can adopt two different values. Therefore, such availability constraints are called bimodal availability constraints. The objective has been to minimise the total completion time. By considering the complexity issues through a mathematical model, a heuristic algorithm with the time complexity of and a branch-and-bound algorithm accompanied with several lemmas and efficient dominance rules are proposed in order to solve the problems optimally. Computational results for 1680 sample problems are employed to demonstrate that the branch-and-bound algorithm is able to solve problems up to 22 jobs and the mean average error for the heuristic algorithm is 1.05%.

A note on resource allocation scheduling with position-dependent workloads

Abstract: In this note, single machine scheduling with concurrent resource allocation and position-dependent workloads is studied. The aim is to find jointly the optimal sequence and the optimal resource allocation. A bicriteria analysis of the problem is provided where the first criterion is to minimize the scheduling cost (i.e. makespan, total completion time, total absolute differences in completion times, total absolute differences in waiting times) and the second criterion is to minimize the total resource consumption cost. It is proved that four bicriteria problems can be solved efficiently.

Single Machine Scheduling with Deteriorating Jobs

Abstract: In this paper we consider a single scheduling problem with release dates concerning time-deteriorating job processing time, where the processing time of a job is a piecewise linear deterioration function of its starting time. The objective of the problem is to minimize the total completion times of jobs. This problem is strongly NP-hard since it is a generalization of the single-machine total completion times 1|r|SigmaCj. We develop the first implementation of the Lagrangian relaxation (LR) for the problem under study. A shorten time horizon strategy is derived to speed-up implementing algorithm of LR. The extensive computational experiments are carried out and the computational results demonstrate that the proposed method is highly effective for our problem in a relatively short computation time.