This work studies a two-stage hybrid flowshop problem with secondary resources (workers). The goal is to minimise the average tardiness. The workers are assigned to the workstations by time buckets ...(work shifts), and the assignment changes during the planning horizon. Two versions of the problem are studied: (i) the case where the average efficiency of the workers determines the time to process jobs; (ii) the case where the efficiency of the slowest worker assigned to a workstation determines the time to process jobs. The problem is NP hard and a set of heuristics are proposed to generate job sequences and worker assignments. Computational experiments are performed on randomly generated test problems. The experiments revealed that the proposed heuristics are able to find a large percentage of the optimal solutions for small sized instances, while on large sized instances the heuristic performance depended on experimental factors.
Given the high variability of both quantity and condition of the returns, closed-loop supply chains depend on a mix of remanufactured and new components. Effectively managing the combined flow of ...returned and new components is imperative to minimize total system costs. This paper proposes a model that helps manage the flow of returns by determining the incentives to offer returners, while simultaneously determining a capacity contract with the supplier of new components. The model considers returns from multiple sources, where each source has different characteristics in terms of the quantity and condition of its returns. The model also accounts for uncertainties from the return sources, as well as the new components supplier. Such uncertainties result in a failure to meet the demand for components, incurring loss costs. Sensitivity analyses of a numerical example were conducted to illustrate the model and gain further insights. The results demonstrate noteworthy relationships between supplier-related costs and those associated with not meeting the required demand, as well as their influence on the incentives to offer and the supplier's capacity contract.
•Components can be sourced new or remanufactured from multiple return sources.•Model determines the capacity to contract from the new component supplier.•Model determines the optimal incentive for each return source.•Costs include losses due to a lack of remanufactured components.•Major interactions exist among incentives, contract capacity and loss costs.
A new unrelated parallel machine scheduling problem with deteriorating effect and the objective of makespan minimization is presented in this paper. The deterioration of each machine (and therefore ...of the job processing times) is a function of the sequence of jobs that have been processed by the machine and not (as considered in the literature) by the time at which each job is assigned to the machine or by the number of jobs already processed by the machine. It is showed that for a single machine the problem can be solved in polynomial time, whereas the problem is NP-hard when the number of machines is greater or equal than two. For the last case, a set of list scheduling algorithms and simulated annealing meta-heuristics are designed and the effectiveness of these approaches is evaluated by solving a large number of benchmark instances.
We propose a decision tree model that considers reverse and forward flows in a closed-loop supply chain (CLSC). Based on observations of three CLSCs, the model considers an environment where there is ...uncertainty in the quantity of returned used components (and new components from suppliers) with the decision being the incentive offered to each return source. Given that there are multiple suppliers, one must determine which supplier(s) to use and the corresponding capacity to reserve, in order to minimise total system costs. An example and a sensitivity analysis are presented to illustrate the model and to investigate multiple scenarios under various conditions. The analysis demonstrates that the supplier portfolio and returner incentive decisions are strongly linked to the supplier reliability, returned quantities, and the costs of not meeting the demand. Furthermore, the analysis suggests that understanding the behaviour of return sources relative to incentives is the most critical variable to implement the model.
The match rate of medical schools in the U.S. has been extensively studied from the perspective of applicants and influential factors. A method to objectively estimate the efficiency of a medical ...school’s match rate has not been described in the literature. Such a method constitutes a significant improvement opportunity for medical schools via benchmarking best practices. This research fills the gap and proposes a bootstrap data envelopment analysis (DEA) framework to assess the residency match rate efficiency of medical schools. The efficacy of the proposed method is confirmed when benchmarking the Texas allopathic medical schools to representative samples of allopathic medical schools in the United States. The model allows to determine the statistical significance of differences in the residency match rate efficiency between groups of medical schools. The proposed bootstrap DEA approach is used to estimate the real efficiency's density function of 40 medical schools in the U.S. over the 2018–2020 period. The aggregate efficiency estimation showed that the medical schools are performing at a high competitive level; they have experienced a slight decline in scale efficiencies and have preserved high managerial performance. The study measured four groups: Texas medical schools, top ten ranked, middle ten ranked, and bottom ten ranked U.S. medical schools. The overall major improvement opportunity for medical schools is the scale of operations. Results confirm that medical schools are shown to be efficient in training future physicians.
•We develop a model for the optimal allocation of demand across a set of suppliers.•It considers multiple demand points and unique transportation costs.•It considers suppliers with unique ...reliability, capacity, and cost variables.•The model provides a baseline allocation to suppliers and contingency plans.•A numerical example is presented to illustrate the model and provide insights.
We consider the optimal allocation of demand across a set of suppliers given the risk of supplier failures. We assume items sourced are used in multiple facilities and can be purchased from multiple suppliers with different cost and reliability characteristics. Suppliers have production flexibility that allows them to deliver a contingency quantity in case other suppliers fail. Costs considered include supplier fixed costs and variable costs per unit, while failure to deliver to a demand point results in a particular financial loss. The model utilizes the decision tree approach to consider all the possible states of nature when one or more suppliers fail, as well as expand the traditional transportation problem. Unlike other supplier selection models, this model considers contingency planning in the decision process, minimizing the total network costs. This results in a base allocation to one or more of the available suppliers and a state of nature specific delivery contingency plan from the suppliers to each demand point. A numerical example, as well as sensitivity analysis, is presented to illustrate the model and provide insights.
This paper addresses the minimal makespan parallel machine problem where machines are subject to preventive maintenance events of a known deterministic duration. The processing time of a job depends ...on its predecessors since the machine's last maintenance. The paper proposes some dominance criteria for sequences of jobs assigned to a machine, and uses these criteria to design constructive heuristics to this NP-hard problem. The computational investigation determines the parameters that make a hard instance and studies the sensitivity of the heuristics to these parameters.
•The model considers the preference of workers to the different types of tasks performed in a parallel shop environment.•The model proposes multiple measures related to worker satisfaction based on ...overall preference and the variety of work.•Experiments are conducted to analyze the relationship between the satisfaction measures and the efficiency of the shop.•Results indicate diverse factors such as the number of job types have an effect on efficiency and worker satisfaction.
The inclusion of worker satisfaction in scheduling problems is of significant importance to many organizations and constitutes a current relevant research stream. This article contributes to the body of knowledge by studying the well-known identical parallel machine scheduling problem while considering workers’ satisfaction. Metrics of job preference and desirable job variety are used to model workers’ satisfaction in the scheduling problem. The tradeoffs between maximum completion time and worker satisfaction are analyzed. The results demonstrate the usefulness of the model, finding efficient schedules, in terms of completion time and worker satisfaction, in a reasonable computational time. Major findings suggest that a higher number of jobs per worker and a wider variety of job types have a positive relationship with workers’ satisfaction when determining work schedules. This research is relevant in practice as it supports the goal of organizations being efficient and of considering the welfare of their employees.
•We model the assignment of technicians to quality control tests.•Research is based on a pharmaceutical manufacturing environment.•Critical considerations are the preferences and capabilities of the ...technicians.•Objective is to maximize technician preferences subject to a maximum difference.•A heuristic was proposed and compared to the optimal solution.
This research addresses the assignment of technicians to quality control tests in a pharmaceutical manufacturing environment. The problem is complex as it includes constraints related to the capabilities of the quality assurance technicians, as well as various criteria related to efficiency, customer service, and worker satisfaction. We consider several factors that are particular to labor scheduling in the pharmaceutical industry: preference to certain types of work and certification related to training in specific tests. We propose and utilize a technician satisfaction metric and develop a heuristic to maximize this measure. Experiments are performed in order to evaluate the performance of the proposed heuristic, and gain insights regarding the relationship among key experimental factors. The results demonstrate that, in general, the proposed heuristic quickly generates scheduling assignments that provide a very good approximation of the optimal solution.
Two important managerial objectives incorporated in production planning are the maximisation of the on-time delivery of orders and worker satisfaction. While the maximisation of on-time deliveries ...has frequently been considered in past production planning research, the component of maximising worker satisfaction has typically been ignored. The assignment of workers to their preferred jobs is an important factor since it results in a productive working environment with high worker performance and a low turnover rate. This study presents a job scheduling model that considers both criteria simultaneously and derives solution approaches to generate non-dominated solutions. The solution approaches are examined under various experimental conditions to evaluate their performance. Finally, a prototype tool developed as a proof of concept is presented.
