A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems

This paper was accepted for publication in the journal International Journal of Bio-Inspired Computation and the definitive published version is available at http://dx.doi.org/10.1504/IJBIC.2015.073165Firefly Algorithm (FA) is a nature-inspired optimization algorithm that can be successfully applied to continuous optimization problems. However, lot of practical problems are formulated as discrete optimization problems. In this paper a hybrid discrete firefly algorithm (HDFA) is proposed to solve the multi-objective flexible job shop scheduling problem (FJSP). FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimization objectives - the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithm’s discretization which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm (DFA) is combined with local search (LS) method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems

Pembrolizumab for patients with leptomeningeal metastasis from solid tumors: efficacy, safety, and cerebrospinal fluid biomarkers

BackgroundThe benefit of immune checkpoint inhibitors (ICIs) in patients with leptomeningeal metastases (LMM) is unknown.MethodsWe undertook a phase II trial of pembrolizumab in patients with LMM from solid tumors. Eligible patients had radiologic/cytologic LMM and Eastern Cooperative Oncology Group performance status 0–1. Pembrolizumab was administered intravenously at 200 mg q3W until disease progression/unacceptable toxicity. The primary endpoint was central nervous system (CNS) response after four cycles, defined radiologically/cytologically/clinically. Serial cerebrospinal fluid (CSF) was assessed for tumor-derived DNA (t-DNA) aneuploidy and cytokines.ResultsThirteen of a planned 16 patients were treated between April 2017 and December 2019. The study closed early for poor accrual. Median age was 57 years (range: 22–79). Sixty-two percent of patients had tumors not traditionally ICI-responsive (hormone-receptor (HR)-positive breast carcinoma=39%; high-grade glioma=23%), while 38% had ICI-responsive tumors (non-small cell lung cancer (NSCLC)=23%, head and neck carcinoma=8%, cutaneous squamous carcinoma (CSC)=8%). CNS response was observed in 38% of patients at 12 weeks (95% CI 13.9% to 68.4%) by pre-defined criteria and LM-RANO, and 2 achieved durable complete responses (CSC=1, overall survival (OS) 3+ years; NSCLC=1, OS 9 months). Median CNS progression-free survival and OS was 2.9 months (95% CI 1.3 to NR) and 4.9 months (95% CI 3.7 to NR), respectively. Grade 3+ treatment-related adverse events occurred in 15% of patients. Sensitivity for LMM detection by t-DNA and cytopathology was 84.6% (95% CI 54.6% to 98.1%) and 53.9% (95% CI 25.1% to 80.8%), respectively. Pre-therapy and on-therapy CSF cytokine analysis demonstrated complete responders clustered together.ConclusionsPembrolizumab conferred a 38% CNS response rate in patients with LMM, a tolerable safety profile, and deep responses in selected patients with ICI-responsive tumors. CSF t-DNA may be sensitive for LMM detection, and immunologic subsets of CNS response warrant further study.Trial registration numberNCT03091478</jats:sec