Minimizing makespan in flowshop with time lags

We consider the problem of minimizing the makespan in a flowshop involving maximal and minimal time lags. Time lag constraints generalize the classical precedence constraints between operations. We assume that such constraints are only defined between operations of the same job. We propose a solution method and present several extensions.Comment: 2 pages. Also available at http://hal.inria.fr/inria-0000014

An exact method for solving the two-machine flow-shop problem with time delays

International audienc

Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

Purpose: Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.Peer Reviewe

Heuristics for scheduling a two-stage hybrid flow shop with parallel batching machines: application at a hospital sterilisation plant

The model of a two-stage hybrid (or flexible) flow shop, with sequence-independent uniform setup times, parallel batching machines and parallel batches has been analysed with the purpose of reducing the number of tardy jobs and the makespan in a sterilisation plant. Jobs are processed in parallel batches by multiple identical parallel machines. Manual operations preceding each of the two stages have been dealt with as machine setup with standardised times and are sequence-independent. A mixed-integer model is proposed. Two heuristics have been tested on real benchmark data from an existing sterilisation plant: constrained size of parallel batches and fixed time slots. Computation experiments performed on combinations of machines and operator numbers suggest balancing the two stages by assigning operators proportionally to the setup time requirements

Permutation flow shops with exact time lags to minimise maximum lateness

International audienceIn this paper we investigate the m-machine permutation flow shop scheduling problem where exact time lags are defined between consecutive operations of every job. This generic model can be used for the study and analysis of various real situations that may arise, for instance, in the food-producing, pharmaceutical and steel industries. The objective is to minimise the maximum lateness. We study polynomial special cases and provide a dominance relation. We derive lower and upper bounds that are integrated in a branch-and-bound procedure to solve the problem. Three branching schemes are proposed and compared. We perform a computational analysis to evaluate the efficiency of the developed method

Job-shop scheduling with approximate methods

Imperial Users onl

Internet of Things (IoT) Utilization to Improve Performance and Productivity of Internal Supply Chain

The inevitable transformations brought about by the rapidly changing Internet of Things (IoT) impact all aspects of life today, including management and businesses. Specifically, areas of businesses depending mainly on internal supply chain capacity are experiencing a paradigm shift to ensure effective company performance regarding purchases, production, company sales, and product distribution. This shift means that challenges faced by the internal chain supply unit can be solved by adopting and adapting IoT as a new way to minimize work delays and save time. Moreover, IoT automatically leads to performance and productivity increases. Therefore, the present paper aims to justify adopting and adapting IoT applications in Indonesian companies, including retail businesses. Most companies’ internal supply chain units face several difficulties during and after the devastating peak of COVID-19, which has led to a total global lockdown. These problems' complexity is exponential and requires innovative ways to solve their prevailing challenges. This study used observation, interview, and documentary research methods through a large-scale survey. The survey obtained the necessary information regarding how companies utilize IoT to improve their performance and productivity without hindering their internal supply chain and production units. The study concluded that the adoption of IoT, if well implemented, leads to a sustainable company and uninterrupted supply chain performance, indicating the proper performance of the organization. Doi: 10.28991/esj-2021-SP1-017 Full Text: PD