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With the increasing attention on environment issues, green scheduling in manufacturing industry has been a hot research topic. As a typical scheduling problem, permutation flow shop scheduling has gained deep research, but the practical case that considers both setup and transportation times still has rare research. This paper addresses the energy-efficient permutation flow shop scheduling problem with sequence-dependent setup time to minimise both makespan as economic objective and energy consumption as green objective. The mathematical model of the problem is formulated. To solve such a bi-objective problem effectively, an improved multi-objective evolutionary algorithm based on decomposition is proposed. With decomposition strategy, the problem is decomposed into several sub-problems. In each generation, a dynamic strategy is designed to mate the solutions corresponding to the sub-problems. After analysing the properties of the problem, two heuristics to generate new solutions with smaller total setup times are proposed for designing local intensification to improve exploitation ability. Computational tests are carried out by using the instances both from a real-world manufacturing enterprise and generated randomly with larger sizes. The comparisons show that dynamic mating strategy and local intensification are effective in improving performances and the proposed algorithm is more effective than the existing algorithms. [ABSTRACT FROM AUTHOR]

Abstract A tsunami generated by an earthquake that occurred off the east coast of Japan in 1611 was predominantly concentrated along the Sanriku Coast. The 1611 event produced its greatest observed tsunami height at Koyadori, 28.8 m, higher than that produced by other representative tsunamis at the same location such as the 2011 Tohoku and 1896 Meiji Sanriku tsunamis. The characteristics of the source that resulted in the remarkable tsunami height at Koyadori have been widely debated. In this study, we simulated the local intensification mechanism of the 1611 tsunami and derived some key characteristics of the earthquake that produced the intensification at Koyadori based on these results. First, we investigated the topographical inundation characteristics in representative areas on the Sanriku Coast, including Koyadori, by numerical means. By comparing the numerical results with the observed heights for the 1611 tsunami, we found that a simulated tsunami that was dominated by short-wave components yielded a promising reproduction of the observed heights. The development of a local resonance seemed a more likely cause for the observed local intensification at Koyadori than a single-pulse wave. These results suggested that the 1611 earthquake produced a tsunami dominated by short-wave components. Furthermore, the source must have been located far off the Tohoku coast near the Japan Trench axis to have had substantial short-wave components along the Sanriku Coast. Based on these findings, we constructed a source scenario for local intensification by investigating the characteristics of Green’s functions from single-point sources. The scenario involves two separate earthquake sources in shallow crustal areas at the plate interface of the subduction zone, resulting in a moment magnitude of 8.5. The tsunami produced by this source model, which reflected the characteristics of a tsunami earthquake, effectively reproduced the local intensification observed on the Sanriku Coast.

A tsunami generated by an earthquake that occurred off the east coast of Japan in 1611 was predominantly concentrated along the Sanriku Coast. The 1611 event produced its greatest observed tsunami height at Koyadori, 28.8 m, higher than that produced by other representative tsunamis at the same location such as the 2011 Tohoku and 1896 Meiji Sanriku tsunamis. The characteristics of the source that resulted in the remarkable tsunami height at Koyadori have been widely debated. In this study, we simulated the local intensification mechanism of the 1611 tsunami and derived some key characteristics of the earthquake that produced the intensification at Koyadori based on these results. First, we investigated the topographical inundation characteristics in representative areas on the Sanriku Coast, including Koyadori, by numerical means. By comparing the numerical results with the observed heights for the 1611 tsunami, we found that a simulated tsunami that was dominated by short-wave components yielded a promising reproduction of the observed heights. The development of a local resonance seemed a more likely cause for the observed local intensification at Koyadori than a single-pulse wave. These results suggested that the 1611 earthquake produced a tsunami dominated by short-wave components. Furthermore, the source must have been located far off the Tohoku coast near the Japan Trench axis to have had substantial short-wave components along the Sanriku Coast. Based on these findings, we constructed a source scenario for local intensification by investigating the characteristics of Green's functions from single-point sources. The scenario involves two separate earthquake sources in shallow crustal areas at the plate interface of the subduction zone, resulting in a moment magnitude of 8.5. The tsunami produced by this source model, which reflected the characteristics of a tsunami earthquake, effectively reproduced the local intensification observed on the Sanriku Coast. [ABSTRACT FROM AUTHOR]

A thermomechanical energy density factor S is derived in terms of the mechanical and thermal stress intensity factors [image omitted] and [image omitted], respectively. While both [image omitted] and [image omitted] can change sign depending on the directions of the applied mechanical stress and thermal gradient, the quadratic form [image omitted], however, is positive definite. The mixed term with A12 can be either positive or negative depending on the sign of [image omitted] and [image omitted]. Hence, S can increase or decrease with the crack length that is contained in the expressions for the intensity factors. Based on the criterion of crack growth similarity with the proportion S/r being equal to the area under the true stress and true strain curve, it is found that crack growth initiation can be enhanced or retarded. If the mechanical stress is fixed in tension, crack growth is enhanced when the thermal gradient is in the direction of crack initiation while the opposite prevails when the direction of thermal gradient is against the direction of crack initiation induced by the mechanical tension. The formulation provides a clear interaction of how the mechanical and thermal effects would compete. Results are obtained for 38Cr2Mo2VA steel, LY12 aluminum and TC6 titanium alloys which are the sequential order of crack growth enhancement and retardation. Such information can assist the correlation of crack growth data when comparing the results for different materials. [ABSTRACT FROM AUTHOR]

To decrease the load of electricity grid during the peak period, time-of-use electricity price has been implemented in industries to shift the production activities from the peak to the off-peak period. This paper addresses the flexible job shop scheduling under time-of-use electricity prices (FJSPTOUEP) to minimize both makespan and total electricity cost (TEC) simultaneously. We present the mixed integer programming model and propose a hybrid multi-objective evolutionary algorithm based on decomposition (HMOEA/D) to solve the problem. To generate an initial population with certain quality and diversity, several rules are used together. In the framework of MOEA/D, a cooperative search operator is designed to generate new solutions by exchanging information of neighbours. To improve the quality of solutions, two local intensification operators are designed by analysing the critical path of the schedule. An adaptive selection strategy is designed based on the reference point for well using the local search operators to enhance exploitation ability. Moreover, according to the characteristics of time-of-use electricity prices, an adjustment strategy is proposed to reduce electricity cost for further improving solutions. Computational results and statistical comparisons show that both the local intensification and adjustment strategy are effective. It also shows that the proposed HMOEA/D is more effective than other optimization algorithms in solving the FJSPTOUEP. • Flexible job shop scheduling under time-of-use electricity prices is studied. • Multi-objective evolutionary algorithm based on decomposition is proposed. • Adaptive selection strategy and adjustment strategy are designed. • Effectiveness is demonstrated by numerical comparisons. [ABSTRACT FROM AUTHOR]

Facing the energy crisis, manufacturers is paying much attention to the energy-efficient scheduling by taking both economic benefits and energy conservation into account. Meanwhile, with the economic globalization, it is significant to facilitate the advanced manufacturing and scheduling in the distributed way. This paper addresses the energy-efficient distributed no-idle permutation flow-shop scheduling problem (EEDNIPFSP) to minimize makespan and total energy consumption simultaneously. By analyzing the characteristics of the problem, several properties are derived. To solve the problem effectively, a collaborative optimization algorithm (COA) is proposed by using the properties and some collaborative mechanisms. First, two heuristics are collaboratively utilized for population initialization to guarantee certain quality and diversity. Second, multiple search operators collaborate in a competitive way to enhance the exploration adaptively. Third, different local intensification strategies are designed for the dominated and non-dominated individuals to enhance the exploitation. Fourth, a speed adjusting strategy for the non-critical operations is designed to improve total energy consumption. The effect of key parameters is investigated using the design-of-experiment with full factorial setting. Comparisons based on extensive numerical tests are carried out, which demonstrate the effectiveness of the proposed algorithm in solving the EEDNIPFSP. • Address energy-efficient distributed no-idle permutation flow-shop. • Collaborative multi-objective optimization algorithm. • Collaborative search in a competitive way. • Enhance exploitation by local intensification strategies. • Improve energy consumption by speed adjusting strategy. [ABSTRACT FROM AUTHOR]