Dataset Information

A mathematical formulation and an NSGA-II algorithm for minimizing the makespan and energy cost under time-of-use electricity price in an unrelated parallel machine scheduling.

ABSTRACT: In many countries, there is an energy pricing policy that varies according to the time-of-use. In this context, it is financially advantageous for the industries to plan their production considering this policy. This article introduces a new bi-objective unrelated parallel machine scheduling problem with sequence-dependent setup times, in which the objectives are to minimize the makespan and the total energy cost. We propose a mixed-integer linear programming formulation based on the weighted sum method to obtain the Pareto front. We also developed an NSGA-II method to address large instances of the problem since the formulation cannot solve it in an acceptable computational time for decision-making. The results showed that the proposed NSGA-II is able to find a good approximation for the Pareto front when compared with the weighted sum method in small instances. Besides, in large instances, NSGA-II outperforms, with 95% confidence level, the MOGA and NSGA-I multi-objective techniques concerning the hypervolume and hierarchical cluster counting metrics. Thus, the proposed algorithm finds non-dominated solutions with good convergence, diversity, uniformity, and amplitude.

SUBMITTER: Rego MF

PROVIDER: S-EPMC9044217 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

A mathematical formulation and an NSGA-II algorithm for minimizing the makespan and energy cost under time-of-use electricity price in an unrelated parallel machine scheduling.

Rego Marcelo F MF Pinto Júlio Cesar E M JCEM Cota Luciano P LP Souza Marcone J F MJF

PeerJ. Computer science 20220203

In many countries, there is an energy pricing policy that varies according to the time-of-use. In this context, it is financially advantageous for the industries to plan their production considering this policy. This article introduces a new bi-objective unrelated parallel machine scheduling problem with sequence-dependent setup times, in which the objectives are to minimize the makespan and the total energy cost. We propose a mixed-integer linear programming formulation based on the weighted su ...[more]

PMID: 35494814

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Project description:BackgroundCost-sharing in health insurance plans creates incentives for patients to shop for lower prices, but it is unknown what price information patients can obtain when scheduling office visits.ObjectiveTo determine whether new patients can obtain price information for a primary care visit and identify variation across insurance types, offices, and geographic areas.DesignSimulated patient methodology in which trained interviewers posed as non-elderly adults seeking new patient primary care appointments. Caller insurance type (employer-sponsored insurance [ESI], Marketplace, or uninsured) and plan were experimentally manipulated. Callers who were offered a visit asked for price information. Unadjusted means and regression-adjusted differences by insurance, office types, and geography were calculated.ParticipantsCalls to a representative sample of primary care offices in ten states in 2014: Arkansas, Georgia, Iowa, Illinois, Massachusetts, Montana, New Jersey, Oregon, Pennsylvania, and Texas (N = 7865).Main measuresCallers recorded whether they were able to obtain a price. If not, they recorded whether they were referred to other sources for price information.Key resultsOverall, 61.8% of callers with ESI were able to obtain a price, versus 89.2% of uninsured and 47.3% of Marketplace callers (P < 0.001 for differences). Price information was also more readily available in small offices and in counties with high uninsured rates. Among callers not receiving a price, 72.1% of callers with ESI were referred to other sources (billing office or insurance company), versus 25.8% of uninsured and 50.9% of Marketplace callers (P < 0.001). A small fraction of insured callers were told their visit would be free. If not free, mean visit prices ranged from $157 for uninsured to $165 for ESI (P < 0.05). Prices were significantly lower at federally qualified health centers (FQHCs), smaller offices, and in counties with high uninsured and low-income rates.ConclusionsPrice information is often unavailable for privately insured patients seeking primary care visits at the time a visit is scheduled.

Dataset Information

A mathematical formulation and an NSGA-II algorithm for minimizing the makespan and energy cost under time-of-use electricity price in an unrelated parallel machine scheduling.

Publications

A mathematical formulation and an NSGA-II algorithm for minimizing the makespan and energy cost under time-of-use electricity price in an unrelated parallel machine scheduling.

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