A common framework and taxonomy for multicriteria scheduling problems with Interfering and competing Jobs: Multi-agent scheduling problems

Most classical scheduling research assumes that the objectives sought are common to all jobs to be scheduled. However, many real-life applications can be modeled by considering different sets of jobs, each one with its own objective(s), and an increasing number of papers addressing these problems has appeared over the last few years. Since so far the area lacks a uni ed view, the studied problems have received different names (such as interfering jobs, multi-agent scheduling, mixed-criteria, etc), some authors do not seem to be aware of important contributions in related problems, and solution procedures are often developed without taking into account existing ones. Therefore, the topic is in need of a common framework that allows for a systematic recollection of existing contributions, as well as a clear de nition of the main research avenues. In this paper we review multicriteria scheduling problems involving two or more sets of jobs and propose an uni ed framework providing a common de nition, name and notation for these problems. Moreover, we systematically review and classify the existing contributions in terms of the complexity of the problems and the proposed solution procedures, discuss the main advances, and point out future research lines in the topic

New scheduling problems with interfering and independent jobs

33 pages. Paper submitted to Journal of scheduling the 8 September 2009.We consider the problems of scheduling independent jobs, when a subset of jobs has its own objective function to minimize. The performance of this subset of jobs is in competition with the performance of the whole set of jobs and compromise solutions have to be found. Such a problem arises for some practical applications like ball bearing production problems. This new scheduling problem is positioned within the literature and the differences with the problems with competing agents or with interfering job set problems are presented. Classical and regular scheduling objective functions are considered and epsilon-constraint approach and linear combination of criteria approach are used for finding compromise solutions. The study focus on single machine and identical parallel machine environments and for each environment, the complexity of several problems is established and some dynamic programming algorithms are proposed

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Exact and Heuristic Algorithms for the Job Shop Scheduling Problem with Earliness and Tardiness Over a Common Due Date

Scheduling has turned out to be a fundamental activity for both production and service organizations. As competitive markets emerge, Just-In-Time (JIT) production has obtained more importance as a way of rapidly responding to continuously changing market forces. Due to their realistic assumptions, job shop production environments have gained much research effort among scheduling researchers. This research develops exact and heuristic methods and algorithms to solve the job shop scheduling problem when the objective is to minimize both earliness and tardiness costs over a common due date. The objective function of minimizing earliness and tardiness costs captures the essence of the JIT approach in job shops. A dynamic programming procedure is developed to solve smaller instances of the problem, and a Multi-Agent Systems approach is developed and implemented to solve the problem for larger instances since this problem is known to be NP-Hard in a strong sense. A combinational auction-based approach using a Mixed-Integer Linear Programming (MILP) model to construct and evaluate the bids is proposed. The results showed that the proposed combinational auction-based algorithm is able to find optimal solutions for problems that are balanced in processing times across machines. A price discrimination process is successfully implemented to deal with unbalanced problems. The exact and heuristic procedures developed in this research are the first steps to create a structured approach to handle this problem and as a result, a set of benchmark problems will be available to the scheduling research community

Heuristic Algorithm to Minimize Total Weighted Tardiness on the Unrelated Parallel Machine with Sequence Dependent Setup and Future Ready Time

This study presents a heuristic algorithm to minimize total weighted tardiness on unrelated parallel machines with sequence-dependent setup time and future ready time. We propose a new rule based on Apparent Tardiness Cost (ATC). The performance of the rule is evaluated on unrelated parallel machines. In order to solve a problem, we use a look-ahead method and a job-swap method. When a machine becomes idle, the heuristic compares the jobs on the machine and selects the one with the smallest total tardiness value to carry out a process. The propose heuristic is divided into three stages: The first stage employs the newly introduced dispatching rule, ATC with continuous setup and ready time for unrelated parallel machines (ATCSR_UP), along with a look-ahead heuristic to select the initial job for each machine. The second stage, consisting of several iterations, schedules the rest of the job on the machine. Each iteration starts by finding the job with the smallest tardiness. The ATCSR_Rm rule proposed by Lin and Hsieh (2013) concerns the unrelated-parallel-machine scheduling which this study examines, so we compare our ATC-based rule with their proposed rule. Although they study a separable setup time in their research, no other paper than Lin and Hsieh (2003) focus on unrelated parallel machine with future ready times. In their WSPT term, they consider the processing time for each job; our own rule considers processing time, setup time, job ready time, and machine time. We consider the setup time, job ready time, and machine time because — according to the continuous sequence-dependent setup rule — setup time should be included in processing time (Yue and Jang 2013). In addition, job ready time and machine time should also be included in the processing time. Adding setup time 〖(s〗_(i,j)), job ready time (r_j), and machine time (t_m) to the formula thus makes the formula more accurate. Lin and Hsieh (2013) use max(r_j,t_i+s_(i,j) ) for the slack term, and they compare the ready time with the sum of the machine available time 〖(t〗_i) and the setup time 〖(s〗_(i,j)). However, in our formula, we consider ready time, machine time, and current time. Current time (t) is used when a job might come at a future time when the machine in question is idle or has finished the job. The last term of the propose heuristic is the ready term, which uses both ready time (r_j) and machine time (t_m), because it needs to specify whether ready time (r_j) or machine time (t_m) goes first. If a job is ready to be processed but the machine is not ready, the job has to wait. We use ready time (r_j) and machine time (t_m) because this makes the formula more suitable for practical, real-world us

Deterministic Assembly Scheduling Problems: A Review and Classification of Concurrent-Type Scheduling Models and Solution Procedures

Many activities in industry and services require the scheduling of tasks that can be concurrently executed, the most clear example being perhaps the assembly of products carried out in manufacturing. Although numerous scientific contributions have been produced on this area over the last decades, the wide extension of the problems covered and the lack of a unified approach have lead to a situation where the state of the art in the field is unclear, which in turn hinders new research and makes translating the scientific knowledge into practice difficult. In this paper we propose a unified notation for assembly scheduling models that encompass all concurrent-type scheduling problems. Using this notation, the existing contributions are reviewed and classified into a single framework, so a comprehensive, unified picture of the field is obtained. In addition, a number of conclusions regarding the state of the art in the topic are presented, as well as some opportunities for future research.Ministerio de Ciencia e Innovación español DPI2016-80750-

Scheduling Single-Machine Problem Oriented by Just-In-Time Principles - A Case Study

Developments in advanced autonomous production resources have increased the interest in the Single-Machine Scheduling Problem (SMSP). Until now, researchers used SMSP with little to no practical application in industry, but with the introduction of multi-purpose machines, able of executing an entire task, such as 3D Printers, replacing extensive production chains, single-machine problems are becoming a central point of interest in real-world scheduling. In this paper we study how simple, easy to implement, Just-in-Time (JIT) based, constructive heuristics, can be used to optimize customer and enterprise oriented performance measures. Customer oriented performance measures are mainly related to the accomplishment of due dates while enterprise-oriented ones typically consider other time-oriented measures.The authors wish to acknowledge the support of the Fundação para a Ciência e Tecnologia (FCT), Portugal, through the grant “Projeto Estratégico – UI 252 – 2011–2012” reference PEst-OE/EME/UI0252/2011 and FCOMP-01-0124FEDER-PEst-OE/EEI/UI0760/2014info:eu-repo/semantics/publishedVersio

Theoretical and Computational Research in Various Scheduling Models

Nine manuscripts were published in this Special Issue on “Theoretical and Computational Research in Various Scheduling Models, 2021” of the MDPI Mathematics journal, covering a wide range of topics connected to the theory and applications of various scheduling models and their extensions/generalizations. These topics include a road network maintenance project, cost reduction of the subcontracted resources, a variant of the relocation problem, a network of activities with generally distributed durations through a Markov chain, idea on how to improve the return loading rate problem by integrating the sub-tour reversal approach with the method of the theory of constraints, an extended solution method for optimizing the bi-objective no-idle permutation flowshop scheduling problem, the burn-in (B/I) procedure, the Pareto-scheduling problem with two competing agents, and three preemptive Pareto-scheduling problems with two competing agents, among others. We hope that the book will be of interest to those working in the area of various scheduling problems and provide a bridge to facilitate the interaction between researchers and practitioners in scheduling questions. Although discrete mathematics is a common method to solve scheduling problems, the further development of this method is limited due to the lack of general principles, which poses a major challenge in this research field