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This paper presents a new model dealing with the job rotation scheduling problem, which is less studied, focusing on human characteristics such as boredom.Existing literature on conceptualizing boredom shows that researchers evaluate boredom in terms of exposure to the same tasks. We developed it to "exposure to similar tasks" and defined its functionality based on the need of assigning jobs with more similarity to each worker in the smallest period of planning which lowers the external interruption effect on worker's concentration. To address the imbalance between number of jobs and that of workers in many industrial settings, we developed a multi-period imbalance assignment model. The proposed model is to rotate workers during a given planning horizon such that the total cost including assignment and boring cost will be minimized. The applicability of the model is described by presenting some real cases and validated through solving several randomly produced test problems by using Lingo software. Two search algorithms, genetic algorithm (GA) and imperialist competitive algorithm (ICA), designed to conquer the algorithmic complexity of model and their parameters adjusted using Taguchi's method were used. The efficiency of algorithms is shown, comparing it with Lingo computation times, and it is shown that ICA solutions have better quality than GA solutions as well.

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Purpose As a critical problem in sophisticated distribution systems, vehicle routing plays a pivotal role in dealing with time windows and capacities constraints. The purpose of this paper is to addresses a new integrated model to incorporate both three-dimensional and time windows aspects of the routing problem. First, capacitated vehicle routing decisions are made subject to a soft time interval to meet the customers’ demands. Afterward, these decisions are entered into the three-dimensional loading problem. Design/methodology/approach The problem is solved using generalized algebraic modeling system software in small-size problems. The problem is NP-hard and requires an efficient solution methodology. For this purpose, a hybrid algorithm has been proposed to solve the large-size problems. The efficiency of this algorithm is checked by making comparisons with exact solutions for small and medium size test problems, and with the related literature for large size problems. Findings The numerical experiments show that the proposed model covers more effectively the broader aspects of the transportation problem. Furthermore, the proposed algorithm supports competitive and satisfactory results by giving reasonable outputs in comparison with previous studies. Originality/value The main purpose of this integration is to achieve minimum total transportation costs, which cannot be guaranteed without applying two referred constraints, simultaneously.

Purpose – The purpose of this paper is to present age-based replacement models subject to shocks and failure rate in order to determine the optimal replacement cycle. As a result, according to system reliability, maintenance costs of the system are to be minimized. Design/methodology/approach – First, the modeling with respect to assumptions and two major factors (shocks and failure rate) is done. Second, by using of MATLAB the optimal parameters are obtained. Finally, analysis of results and comparison of models are done. Findings – Analysis of results shows all models provide optimal replacement cycle and at this time, cost rate of the system by considering the reliability rate is minimal. Also with an increase of one unit to two units, reliability rate increases much higher than the rate of cost. Originality/value – This work provides models that in addition to considering the failure rate (internal factors), also shocks as an external factor have been considered. By considering these two factors more comprehensive and adaptable models have been proposed.