Article
Computer Science, Interdisciplinary Applications
Gang Wang
Summary: This paper addresses an integrated scheduling problem in an e-commerce supply chain, aiming to minimize total costs including shipping and penalties. By formulating a mixed-integer nonlinear program and developing a hybrid particle swarm optimization algorithm, a suitable solution is found within a reasonable time, with computational testing confirming robust and efficient performance of the proposed algorithm.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Software Engineering
Alex Dunbar, Saumya Sinha, Andrew J. Schaefer
Summary: This paper presents continuous, convex hull, and Lagrangian relaxations for multiobjective integer programs (MOIPs) and examines their relationships. It shows that the Lagrangian relaxation can provide tighter bounds than the convex hull relaxation. Additionally, it generalizes the integer programming value function to MOIPs and defines set-valued and vector-valued superadditive duals.
MATHEMATICAL PROGRAMMING
(2023)
Article
Computer Science, Artificial Intelligence
Mojahid Saeed Osman
Summary: This paper introduces an algorithmic method that hybridizes solution procedures with an optimization model to solve the problem of scheduling and allocating changeover tasks. Three priority rules are identified and investigated as objective functions to minimize total changeover time and maximize worker utilization, while satisfying task-sequence-dependency and worker-limit constraints. The proposed hybrid approach provides effective changeover time and worker utilization.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Young-Bin Woo, Ilkyeong Moon, Byung Soo Kim
Summary: This paper introduces a new production-inventory control model for a vertically integrated supply chain network, aiming to minimize total network cost and prevent inventory shortages and shutdown periods. Closed-form functions and a mixed-integer linear programming formulation are proposed, along with an algorithm to reduce computational burden. A case study demonstrates the application of the proposed model.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Pedro M. Castro
Summary: Most short-term scheduling formulations in Process Systems Engineering assume uninterrupted time horizon. However, local working patterns may prevent activities during nights or weekends. This paper presents a problem involving a multiproduct batch chemical plant with stable and unstable intermediates, limited availability of shared resources, non-instantaneous transfer times, and the possibility of interrupting changeover tasks. The proposed Resource-Task Network (RTN) model captures these features and preemption of changeover tasks is found to be beneficial.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Engineering, Industrial
Mark Baxendale, James M. McGree, Aaron Bellette, Paul Corry
Summary: This paper explores production scheduling for rotomoulded plastics manufacturing in a multi-machine environment to minimize total tardiness. Simulated annealing and tabu search algorithms, along with a constructive heuristic, were developed to achieve near-optimal solutions within a practical time-frame. The algorithms were tuned and tested using randomly generated problem instances representative of a production environment in Queensland, Australia, with simulated annealing generally yielding the best results in solution quality.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Industrial
Fayez F. Boctor
Summary: This paper deals with a more realistic version of the lot sizing and scheduling problem, where a single machine processes different products. The objective is to minimize the sum of setup costs and inventory holding costs. The paper presents a mathematical formulation of the problem and two specially designed solution heuristics.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Transportation Science & Technology
Mohsen Parsafard, Xiaopeng Li
Summary: This study focuses on integrating human mobility characteristics into sensor location design, investigating moving object trajectories, and constructing a probabilistic network structure to quantify human presence probability at different times and locations. It proposes a MINLP model to maximize spatial and temporal coverage of targets, testing greedy heuristic, simulated annealing and Lagrangian relaxation algorithms for obtaining near optimal solutions. Performance of the proposed model is demonstrated on hypothetical and real-world numerical examples with promising results.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Mathematics
Drazen Popovic, Nenad Bjelic, Milorad Vidovic, Branislava Ratkovic
Summary: This study addresses the production lot-sizing and scheduling problem in the fruit juice production industry. An enhanced inventory management perspective is taken into account, incorporating additional aspects such as shelf-life concept, limited warehouse capacity, and outsourcing potential. Models including mixed integer linear programming and hybrid variable neighborhood search with linear programming are developed to minimize total costs. The results provide insights into the impact of different input parameters on the production process, enabling decision makers to improve efficiency in changing conditions.
Article
Thermodynamics
Verena Halmschlager, Rene Hofmann
Summary: Holistic energy efficiency solutions are crucial for minimizing energy consumption in today's industry, while incorporating production scheduling into energy optimization can significantly enhance energy efficiency.
Article
Computer Science, Interdisciplinary Applications
Jonghwa Lee, Byung-In Kim, Sang Hun Kim
Summary: This study introduces the block assignment problem in long-term production planning for a shipbuilder and proposes a two-stage matheuristic algorithm to solve it. The algorithm yields remarkable reductions in assignment costs and factory workload violations compared with manual planning, as demonstrated by computational experiments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Shamik Misra, Lucas Ryan Buttazoni, Venkatachalam Avadiappan, Ho Jae Lee, Martin Yang, Christos T. Maravelias
Summary: This article introduces a web-based application called CProS, which aims to assist researchers in generating and solving chemical production scheduling instances. The application provides a user interface for defining instances using the state-task network representation and automatically generates a corresponding mixed-integer linear programming model. Users also have the option to choose different solution methods.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Management
Shayan Tavakoli Kafiabad, Masoumeh Kazemi Zanjani, Mustapha Nourelfath
Summary: This study proposes a multistage stochastic programming model for operations planning under independent random demand. A decomposition heuristic is developed to efficiently solve the problem by decomposing the model into submodels and coordinating them via a subgradient algorithm to obtain a high-quality feasible solution.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Tristan Becker, Maximilian Schiffer, Grit Walther
Summary: In this paper, a general algorithmic framework for rotating workforce scheduling is proposed. The framework utilizes graph representation and branch-and-cut approach to solve various practical problem variants. The computational studies show that the framework is state-of-the-art in rotating workforce scheduling and exhibits consistent computational performance.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Ece Yagmur, Saadettin Erhan Kesen
Summary: The study investigates a joint production scheduling and outbound distribution planning problem, using a mixed integer programming formulation and genetic algorithm to reduce delivery delays and vehicle travel time, proposing a new splitting procedure. Experimental results indicate that genetic algorithm outperforms simulated annealing in terms of solution quality for medium and large instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
