Abstract
Re-entrant hybrid flow shop scheduling problem (RHFSP) is widely used in industries. However, little attention is paid to energy consumption cost with the raise of green manufacturing concept. This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. A right-shift operation is then used to adjust the starting time of operations by avoiding the period of high electricity price to reduce the energy consumption cost as far as possible. The experimental results show that IMOALO algorithm is superior to multiobjective ant lion optimization (MOALO) algorithm, NSGA-II, and MOPSO in terms of the convergence, dominance, and diversity of nondominated solutions. The proposed model can make enterprises avoid high price period reasonably, transfer power load, and reduce the energy consumption cost effectively. Meanwhile, parameter analysis indicates that the period of TOU electricity tariffs and energy efficiency of machines have great impact on the scheduling results.
Highlights
Re-entrant hybrid flow shop scheduling problem (RHFSP) is a combination of classic hybrid flow shop scheduling problem and re-entrant scheduling problem
It can be seen from the figure that Ω measures of improved multiobjective ant lion optimization (IMOALO) are greater than in other algorithms; Δ and Ω measures of IMOALO are smaller than in other algorithms significantly, which further verifies the conclusion
In the vicinity where 45 hours and 75 hours are the periods with low electricity price, the total energy consumption of all machines increases after the right-shift procedure; on the contrary, in the vicinity where 55 hours and 115 hours are the periods with high electricity price, the total energy consumption of all machines decreases after the right-shift procedure
Summary
Re-entrant hybrid flow shop scheduling problem (RHFSP) is a combination of classic hybrid flow shop scheduling problem and re-entrant scheduling problem. Luo et al [17] addressed the multiobjective ant colony optimization algorithm to solve the hybrid flow shop scheduling problem with unrelated parallel machines under TOU electricity tariffs aiming at minimizing the makespan and energy consumption cost. Mikhaylidi et al [22] studied the production and operation scheduling problem of rechargeable batteries under TOU electricity tariffs using a dynamic programming algorithm, aiming at minimizing total power consumption and delaying penalty cost. Some achievements have been made in this field, the research on green job shop scheduling under TOU electricity tariffs is still immature, and the study on RHFSP with unrelated parallel machines considering energy consumption cost is even less. Is paper proposes the improved multiobjective ant lion optimization (IMOALO) algorithm with right-shift operation to approximate the Pareto optimal solutions for RHFSP under TOU electricity tariffs with the objective of minimizing the makespan and energy consumption cost.
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