Scheduling Theory and Algorithms for Sustainable Manufacturing (2025)

Special Issue on Scheduling Theory and Algorithms for Sustainable Manufacturing

Algorithms, 2025

This is the Editorial of a special issue on Scheduling Theory and Algorithms for Sustainable Manufacturing with 11 published papers in the hjournal Algorithms.

Rescheduling in job-shop problems for sustainable manufacturing systems

Journal of Cleaner Production, 2016

Manufacturing industries are faced with environmental challenges so their industrial processes must be optimized in terms of both profitability and sustainability. Most of these processes are dynamic, so the previously obtained solutions cannot be valid after incidences or disruptions. This paper is focused on recovery in dynamic job-shop scheduling problems where machines can work at different rates. Machine speed scaling is an alternative framework to the on/off control framework for production scheduling. Thus, given a disruption, the main goal is to recover the original solution by rescheduling the minimum number of tasks. To this end, a new match-up technique is developed to determine the rescheduling zone and a feasible reschedule. Then, a memetic algorithm is proposed for finding a schedule that minimize the energy consumption within the rescheduling zone but maintaining the makespan constraint. An extensive study is carried out to analyze the behavior of our algorithms to recover the original solution and minimize the energy reduction in different benchmarks, taken from the OR-Library. The energy consumption and processing time of the involved tasks in the rescheduling zone will play an important role to determine the best match-up point and the optimized rescheduling. Upon a disruption, different rescheduling solutions can be obtained, all of them holding with the requirements , but with different values of energy consumption. The results proposed in this paper may be useful to be applied in real industries for energy-efficient production rescheduling.

An energy-cost-aware scheduling methodology for sustainable manufacturing

With the rising energy price and the ever-increasing consciousness of environmental friendliness, it is becoming practically helpful for manufacturers to have a clear view on how the energy is consumed at their shop floors, what the corresponding energy cost is, and how to reduce the energy consumption or the energy cost. However, there is currently limited literature investigating the energy cost minimization in manufacturing through production scheduling under volatile energy prices. This paper proposes a generic mixed-integer linear programming model to enable the job scheduling on a single machine for the purpose of minimizing the necessary energy cost without exceeding the due date. The results given by a case study on a surface grinding machine demonstrate this scheduling methodology effectively contributes to the reduction of greenhouse gas emissions during peak time periods by shifting the production load to off-peak periods, and leads to energy-efficient, demand-responsive, and cost-effective manufacturing processes.

A Keyword, Taxonomy and Cartographic Research Review of Sustainability Concepts for Production Scheduling in Manufacturing Systems

Sustainability

The concept of sustainability is defined as composed of three pillars: social, environmental, and economic. Social sustainability implies a commitment to equity in terms of several “interrelated and mutually supportive” principles of a “sustainable society”; this concept includes attitude change, the Earth’s vitality and diversity conservation, and a global alliance to achieve sustainability. The social and environmental aspects of sustainability are related in the way sustainability indicators are related to “quality of life” and “ecological sustainability”. The increasing interest in green and sustainable products and production has influenced research interests regarding sustainable scheduling problems in manufacturing systems. This study is aimed both at reducing pollutant emissions and increasing production efficiency: this topic is known as Green Scheduling. Existing literature research reviews on Green Scheduling Problems have pointed out both theoretical and practical aspect...

Scheduling in manufacturing systems: new trends and perspectives

International Journal of Production Research

View related articles View Crossmark data Citing articles: 2 View citing articles EDITORIAL Scheduling in manufacturing systems: new trends and perspectives This special issue is dedicated to the celebration of the 55th anniversary of International Journal of Production Research and its relevancy in scheduling. The idea was to present the state-of-the-art in scheduling with respect to theoretical advances as well as practical relevancy in modern manufacturing and resource planning. Thus, the aim of this issue was to attract highquality papers on most recent developments in modelling and solving scheduling problems in manufacturing systems which include parallel as well as multi-stage facilities, the wide area of logistics, supply chains or new applications. Potential authors were encouraged to submit their best recent research particularly in new and challenging scheduling areas leading to advanced perspectives in scheduling. As possible current research topics, we suggested for instance grouping and sequencing operations in multi-stage systems, new scheduling approaches for flexible shops, new developments for scheduling with precedence constraints, batching and further technological constraints, assembly flow shop scheduling, scheduling with setup times/cost, justin-time scheduling, new types of scheduling heuristics and approximation algorithms, scheduling under resource constraints, connections between scheduling and logistics, scheduling problems related to energy management, game theoretic aspects in scheduling, scheduling in segments of a supply chain, scheduling under uncertainty, online scheduling, or new scheduling applications in logistics, traffic, health care, mechanical and industrial engineering, human-computer interaction. We have received 56 submissions. After a careful refereeing, 12 papers have been selected for inclusion into this special issue. The first four papers deal with generalisations of classical single and multi-machine shop scheduling problems. Lai et al. (2017) address the single machine problem of minimising total weighted completion times with interval processing times. The authors introduce the optimality box as a stability measure of an optimal schedule and derive a linear time algorithm for calculating the optimality box for a given job sequence. Properties of an optimality box and a dynamic programming algorithm for constructing a job sequence with the largest optimality box are presented. Computational results for finding a permutation with the largest perimeter of the optimality box are given for instances with up to 10,000 jobs. Valledor et al. (2018) consider a multi-objective rescheduling problem in a dynamic permutation flow shop environment with three types of disruption, namely arrival of new jobs, machine breakdowns and variations in the processing times of the jobs. A rescheduling architecture based on a predictive-reactive strategy and a new method for calculating the reactive schedule in each rescheduling period is suggested. In addition, a methodology with the use of multi-objective performance metrics is used to evaluate dispatching rules. The results demonstrate that the random rule provides a better behaviour than the other rules tested and also a lower ratio of non-dominated solutions in comparison with the apparent tardiness cost and first-in-first-out rules. Meng et al. (2017) investigate a two-stage machining and welding scheduling problem with minimising the sum of the makespan values of the parts, denoted as total makespan. At stage one, several parts are processed as in a job shop scheduling problem and are then grouped into a single construction component at the subsequent welding stage. After presenting a mathematical model, the authors suggest an improved harmony search algorithm including a local search. It turned out that the new hybrid algorithm outperforms several conventional algorithms. Bozek and Werner (2017) study a flexible job shop scheduling problem with the additional inclusion of lot streaming and sublot size optimisation. The authors suggest a two-stage algorithm, which first minimises the makespan for the smallest sublots. Then the sublots are maximised in the second stage without increasing the makespan. In the second stage, two optimisation criteria are used: the maximisation of the sum of the sublot sizes of all operations and the maximisation of the number of operations that do not need to be split. For solving the problem, mixed integer linear programming, constraint programming and graph-based methods are used. The two developed optimisation approaches are compared for each stage and objective, where benchmark instances with up to 20 jobs and 20 machines are considered. The next two papers deal with particular manufacturing systems, inspired by real production systems. De Matta (2017) considers a manufacturing process appearing in a drug packaging company. The problem requires to assign resources to

Manufacturing Operations Scheduling Based in a Multidimensional Sustainable Manufacturing Index (SMIik)

Circular Economy and Sustainability, 2023

Many essential human needs can only be satisfied through goods and services provided by industry. The products of industry form the material basis of contemporary living standards. All nations rightly require and aspire to efficient industrial bases to satisfy changing needs (Brundtland in U N Comm 4:300 [1]). This aspiration has led nations into a race for industrialization, and this race, as well recognized by the Bruntland Report (Our Common Future, 1987), requires the permanent use of raw materials, constant increases in productivity, and generation of material goods in large quantities which have imposed a very high economic cost, as well as a heavy burden of environmental impacts (Brundtland in U N Comm 4:300 [1]). This document presents a production scheduling proposal for a manufacturing system, based on the maximization of the sustainable manufacturing index (SMI ik) of each of the products to be manufactured. This model manages to develop a utility function that integrates the main dimensions that make up sustainable business development, offering a broader criterion than just economic utility as an element for making the production decision of a manufacturing system. Furthermore, it restricts this function to product demand and the capacity of the production system. In addition, it determines the existing correlation between the sustainable development (SD) dimensions, leading to the decision taken to seek a favorable correlation between them. This model makes it possible to obtain a production sequence oriented to the prioritization of those products that offer a greater contribution to business sustainability, offering, to decision-maker, a novel and synergic option to production scheduling.

Addressing the gap in scheduling research: a review of optimization and heuristic methods in production scheduling

International Journal of Production Research, 1993

Multiobjective approach for deteriorating jobs scheduling for a sustainable manufacturing system

The International Journal of Advanced Manufacturing Technology, 2018

With ever-increasing concerns about climate change, and in the context of diminishing fossil energy resources, energy consumption has become a subject of great importance. In this framework, our study is concerned with the reduction of the energy consumed by a manufacturing system composed of several unrelated parallel machines. We investigate the problem of scheduling a set of n deteriorating jobs on m parallel unrelated machines subject to a deterioration effect, where the processing time of each job is a linear deterioration function of the starting time. The objective is to determine the best scheduling of the jobs, minimizing the makespan and the total energy consumption. We implement a nondominated sorting-based multiobjective algorithm (NSGA-II)-based approaches with a given scheduling rules to solve the developed mathematical model of the considered problem. The performance of the proposed approaches are compared with an exact algorithm and evaluated through computational experiments. Then, we give a multiobjective decision-making method based on the TOPSIS (technique for order of preference by similarity to ideal solution) technique to determine the best solution from the Pareto front according to the decision-maker's preferences.

Special Issue: New Developments in Scheduling and Manufacturing

Optimisation-based scheduling: A discrete manufacturing case study

Computers & Industrial Engineering, 2005

This work presents the development and implementation of a production scheduling system for an electrical appliance manufacturer. Based on recent advances in optimisation-based scheduling approaches, two different software architectures based on two different scheduling formulations, namely the RTN and the STN, are proposed to integrate information available in the different production units and stages with formal algorithmic tools. Optimization results indicate that significant economic benefits can be achieved (e.g. minimization of total operating costs) while ensuring full customer satisfaction as opposed to normal practices followed in the company relying on human expertise. The work indicates that it is possible to solve real-life manufacturing problems using optimization-based approaches but the integration of information in a timely fashion seems to be a major factor in successfully implementing the system and fully realizing its benefits. q (L.G. Papageorgiou).