A bi-objective model for the single-machine scheduling problem with rejection cost and total tardiness minimization

We study the problem of scheduling jobs on a single machine with a rejection possibility, concurrently minimizing the total tardiness of the scheduled jobs and the total cost of the rejected ones. The model we consider is fully bi-objective, i.e. its aim is to enumerate the Pareto front. We tackle the problem both with and without the presence of hard deadlines. For the case without deadlines, we provide a pseudo-polynomial time algorithm, based on the dynamic program of Steiner and Zhang (2011), thereby proving that the problem is weakly NP-hard. For the case with deadlines, we propose a branch-and-bound algorithm and prove its efficiency by comparing it to an \u3b5-constrained approach on benchmark instances based on those proposed in the literature on similar problems

New Solution Approaches for Scheduling Problems in Production and Logistics

The current cumulative PhD thesis consists of six papers published in/submitted to scientific journals. The focus of the thesis is to develop new solution approaches for scheduling problems encountering in manufacturing as well as in logistics. The thesis is divided into two parts: “ma-chine scheduling in production” and “scheduling problems in logistics” each of them consisting three papers. To have most comprehensive overview of the topic of machine scheduling, the first part of the thesis starts with two systematic review papers, which were conducted on tertiary level (i.e., re-viewing literature reviews). Both of these papers analyze a sample of around 130 literature re-views on machine scheduling problems. The first paper use a subjective quantitative approach to evaluate the sample, while the second papers uses content analysis which is an objective quanti-tative approach to extract meaningful information from massive data. Based on the analysis, main attributes of scheduling problems in production are identified and are classified into sever-al categories. Although the focus of both these papers are set to review scheduling problems in manufacturing, the results are not restricted to machine scheduling problem and the results can be extended to the second part of the thesis. General drawbacks of literature reviews are identi-fied and several suggestions for future researches are also provided in both papers. The third paper in the first part of the thesis presents the results of 105 new heuristic algorithms developed to minimize total flow time of a set of jobs in a flowshop manufacturing environ-ment. The computational experiments confirm that the best heuristic proposed in this paper im-proves the average error of best existing algorithm by around 25 percent. The first paper in second part is focused on minimizing number of electric tow-trains responsi-ble to deliver spare parts from warehouse to the production lines. Together with minimizing number of these electric vehicles the paper is also focused to maximize the work load balance among the drivers of the vehicles. For this problem, after analyzing the complexity of the prob-lem, an opening heuristic, a mixed integer linear programing (MILP) model and a taboo-search neighborhood search approach are proposed. Several managerial insights, such as the effect of battery capacity on the number of required vehicles, are also discussed. The second paper of the second part addresses the problem of preparing unit loaded devices (ULDs) at air cargos to be loaded latter on in planes. The objective of this problem is to mini-mize number of workers required in a way that all existing flight departure times are met and number of available places for building ULDs is not violated. For this problem, first, a MILP model is proposed and then it is boosted with a couple of heuristics which enabled the model to find near optimum solutions in a matter of 10 seconds. The paper also investigates the inherent tradeoff between labor and space utilization as well as the uncertainty about the volume of cargo to be processed. The last paper of the second part proposes an integrated model to improve both ergonomic and economic performance of manual order picking process by rotating pallets in the warehouse. For the problem under consideration in this paper, we first present and MILP model and then pro-pose a neighborhood search based on simulated annealing. The results of numerical experiment indicate that selectively rotating pallets may reduce both order picking time as well as the load on order picker, which leads to a quicker and less risky order picking process

Aplicação de simulação para análise do makespan devido á inserção e/ou desistência de tarefas no problema de sequeciamento de produção em uma máquina

Orientador : Prof. Dr. Cassius Tadeu ScarpinCoorientador : Prof. Dr. José Eduardo Pécora JúniorDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 17/02/2016Inclui referências : f.75-77Área de concentração: Programação matemáticaResumo: A necessidade de aproximar modelos encontrados na literatura a sistemas dinâmicos tem motivado grande parte das pesquisas recentes. O presente trabalho aborda o problema de sequenciamento de produção em uma única máquina com o objetivo minimizar o instante de término de processamento de todas as tarefas neste sistema produtivo, ou seja, minimizar o makespan. Neste processo, a geração de novos eventos que ocorram durante o sequenciamento representa a aleatoriedade constatada em problemas reais de produção. Os eventos citados podem ser classificados em tarefas a serem reinseridas no processo de acordo com a ocorrência de novos pedidos ou desistência de pedidos por decisão dos clientes. Uma simulação é criada para tal procedimento. Nele, características como quais tarefas serão reavaliadas ao longo do sequenciamento e em que momento as mesmas ocorrem são consideradas dados estocásticos. A partir destas informações, a simulação é aplicada a um modelo de Programação Linear Inteira Mista (MILP) e também a heurísticas, cujos resultados são comparados ao encontrado no modelo exato. Cinco cenários foram criados para tal avaliação: apenas inserções, mais inserções do que desistências, chegadas e saídas de pedidos em uma mesma proporção, mais desistências do que inserções e, por fim, apenas desistências. Os testes computacionais foram implementados em Visual Basic Studio e obtidos pelo software CPLEX. As respostas obtidas mostram que o conjunto de modelos exatos de cada teste gerado, fornece o melhor resultado dentre os métodos propostos para todos os testes realizados. Palavras-Chave: Minimização do makespan. Re-sequenciamento em uma única máquina. Simulação. Inserção e/ou desistência de novos pedidos.Abstract: The need to approximate models found in literature to dynamic systems has motivated a large part of recent researches. This paper addresses the production-scheduling problem on a single machine in order to minimize the total processing time of all tasks in this production system, called makespan. In this process, the generation of events that occur during sequencing, represents the randomness observed in real production problems. The mentioned events can be classified into tasks to be reinserted in the process according to new orders, or withdrawal of requests by customer decision. A simulation is created for such procedure. In it, variables such as which tasks will be reassessed throughout the sequence and at what time they occur are considered stochastic data. From this information, the simulation is applied to a Mixed Integer Linear Programming model (MILP) and some heuristics, whose results are compared to that found in the exact model. Five scenarios were designed for this evaluation: Only inserts, more inserts than withdrawals, arrival and departure of requests in balance, more withdrawals than insertions and, finally, only withdrawals. The computational tests were implemented in Visual Basic Studio and optimized using the CPLEX software. The responses show that the set of the exact models of each generated test provides the best results among the proposed methods for all the tests. Keywords: Makespan minimization. Rescheduling in a Single Machine. Simulation. Insertion and/or withdrawal of new orders

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum