Abstract
Job selection and scheduling are among the most important decisions for production planning in today's manufacturing systems. However, the studies that take into account both problems together are scarce. Given that such problems are strongly NP-hard, this paper presents an approach based on two heuristic algorithms for simultaneous job selection and scheduling. The objective is to select a subset of jobs and schedule them in such a way that the total net profit is maximized. The cost components considered include jobs' processing costs and weighted earliness/tardiness penalties. Two heuristic algorithms; namely scatter search (SS) and simulated annealing (SA), were employed to solve the problem for single machine environments. The algorithms were applied to several examples of different sizes with sequence-dependent setup times. Computational results were compared in terms of quality of solutions and convergence speed. Both algorithms were found to be efficient in solving the problem. While SS could provide solutions with slightly higher quality for large size problems, SA could achieve solutions in a more reasonable computational time
Highlights
When several jobs or projects are put forward, a manufacturing company may logically tend to choose the ones which deliver the highest return
Given that such problems are strongly NP-hard, this paper presents an approach based on two heuristic algorithms for simultaneous job selection and scheduling
The 80-job instance problem is presented to show the performance of the proposed heuristics to solve large size real world problems
Summary
When several jobs or projects are put forward, a manufacturing company may logically tend to choose the ones which deliver the highest return. Lateness is usually defined as the algebraic difference between the due date and actual completion time of a job, regardless of their mathematical sign It is either in the form of tardiness, which considers only positive difference (completion after due date), or earliness, which corresponds to negative deviation from completion time (ahead of due date) (Conway et al, 2012). According to the just-in-time (JIT) philosophy, a product or service should be produced at the time needed and in the quantities required; otherwise a penalty is incurred in proportion to the amount of lateness (Shingo, 1989) Assigning such penalties prevents extra costs to be imposed to the company by decreasing the amount of inventory of finished products (for earliness) as well as avoiding the loss of goodwill and customer dissatisfaction (for tardiness) (Behnamian & Zandieh, 2013)
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