Abstract
AbstractHybrid sorting immune simulated annealing technique (HSISAT), a Meta - heuristic is proposed for solving the multi objective flexible job-shop scheduling problem (FJSP). The major objectives are distributing the time of machines among the set of operations and scheduling them to minimize the criterion (makespan, total workload and maximum workload). The processing time is sorted for isolating the critical machines and immune simulated annealing (ISA) is applied to increase the convergence speed. Several case studies have been taken from the literature to demonstrate the convergence speed of the proposed algorithm. The computational results have proved that the proposed hybrid algorithm is an effective approach to solve the multi-objective FJSP.
Highlights
The aim of scheduling problems is to allocate resources for execution of operations by satisfying single or a set of objectives and constraints [1]
We propose an integrated approach based on hybridizing sorting simulated annealing [19, 20] algorithm and immune algorithm to solve flexible job shop scheduling (JSP)
We propose hybrid sorting immune simulated annealing algorithm for multi objective Job shop scheduling problem
Summary
The aim of scheduling problems is to allocate resources for execution of operations by satisfying single or a set of objectives and constraints [1] These scheduling problems arise in varieties of production, project, service organizations and supply chain networks where constraints such as definite sequences and limited resources exist [2,3,4,5]. In solving multi objective problems using SA significantly requires a hybrid algorithm for improving the computational time for reaching optimal solution [18]. We propose an integrated approach based on hybridizing sorting simulated annealing [19, 20] algorithm and immune algorithm to solve flexible JSP. The last section presents concluding remarks of our work
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