One-Machine Scheduling with Time-Dependent Capacity via Efficient Memetic Algorithms

This paper addresses the problem of scheduling a set of jobs on a machine with time-varying capacity, with the goal of minimizing the total tardiness objective function. This problem arose in the context scheduling the charging times of a fleet of electric vehicles and it is NP-hard. Recent work proposed an efficient memetic algorithm for solving the problem, combining a genetic algorithm and a local search method. The local search procedure is based on swapping consecutive jobs on a C-path, defined as a sequence of consecutive jobs in a schedule. Building on it, this paper develops new memetic algorithms that stem from new local search procedures also proposed in this paper. The local search methods integrate several mechanisms to make them more effective, including a new condition for swapping pairs of jobs, a hill climbing approach, a procedure that operates on several C-paths and a method that interchanges jobs between different C-paths. As a result, the new local search methods enable the memetic algorithms to reach higher-quality solutions. Experimental results show significant improvements over existing approaches.

Learning ensembles of priority rules for online scheduling by hybrid evolutionary algorithms

This paper studies the computation of ensembles of priority rules for the One Machine Scheduling Problem with variable capacity and total tardiness minimization. Concretely, we address the problem of building optimal ensembles of priority rules, starting from a pool of rules evolved by a Genetic Programming approach. Building on earlier work, we propose a number of new algorithms. These include an iterated greedy search method, a local search algorithm and a memetic algorithm. Experimental results show the potential of the proposed approaches.

An Improved Branch-and-Bound Algorithm for the One-Machine Scheduling Problem with Delayed Precedence Constraints

In this paper, we discuss the one-machine scheduling problem with release and delivery times with the minimum makespan objective. Both heuristics and branch-and-bound algorithms have been formulated for the problem. One such branch-and-bound algorithm solves the problem and a variation that requires a delay between the completion of one job and the start of another (delayed precedence constraints). This paper analyzes key components of this branch-and-bound algorithm and proposes an improved heuristic to be used in conjunction with a different search strategy. Computational experiments demonstrate that the modifications lead to substantial improvements in running time and number of iterations on the one-machine problem instances both with and without delayed precedence constraints.

PENERAPAN JOB SHOP SCHEDULING DENGAN ONE-MACHINE SCHEDULING UNTUK PRODUKSI FURNITURE DI UD. MANDIRI MEUBEL DAN FURNITURE BOJONEGORO

Mebel adalah suatu perabot yang diperlukan seperti barang yang dapat dipindah-pindahkan untuk melengkapi rumah, kantor, dsb. Mebel juga disebut furniture. Bahan yang paling mahal adalah kayu jati. Tradisi membuat kerajinan mebel dan ukir-ukiran kayu jati di Bojonegoro sudah turun temurun dan terkenal dengan kualitasnya. Kerajinan kayu jati ini membuka peluang usaha di Bojonegoro dengan adanya beberapa pengrajin yang mendirikan Usaha Dagang (UD). Permasalahan biasanya muncul ketika pesanan yang dikerjakan tidak bisa memenuhi target konsumen karena terjadi keterlambatan produksi. Untuk menyelesaikan permasalahan ini diperlukan penjadwalan produksi. Tujuan penelitian ini adalah menerapkan job shop scheduling dengan one-machine scheduling untuk penjadwalan produksi furniture di UD. Mandiri Meubel dan Furniture Bojonegoro. Metode yang digunakan adalah job shop scheduling dengan one-machine scheduling berdasarkan tujuh kaidah prioritas dengan bantuan software POM-QM dan pertimbangan multi-starting days. Sumber data penelitian adalah data primer yang diperoleh melalui proses wawancara dengan pemilik UD pada bulan maret 2020. Hasil penelitian ini diperoleh penjadwalan terbaik adalah shortest processing time (SPT) dengan rata-rata keterlambatan sebesar 39 hari. Penelitian ini memberikan kesimpulan bahwa penggunaan job shop scheduling dengan one-machine scheduling dan pertimbangan multi-starting days sangat sesuai diterapkan untuk penjadwalan produksi furniture di UD. Penjadwalan terbaik jatuh pada penjadwalan SPT dengan penjadwalan Moore sebagai alternatifnya

Common Due-Date Assignment and Job Scheduling on Single Machine and Parallel Machines

In this paper we consider a total penalty for the n job, one machine scheduling problem in which all jobs have a common due date. This penalty function is based on the due date value and on the earliness or the lateness of each job in the selected sequence. The main objective is to determine the optimal value of this due date and an optimal sequence to minimize a total penalty function. We prove that the optimal due date result can be generalized to the parallel machine problem. The problem of simultaneously available jobs on several parallel and identical machines. The problem is to find the optimal due date, assuming this to be the same for all jobs and we present a simple heuristic to find an approximate solution. On the basis of a limited experiment, we observe that the heuristic is very effective solution.