Discrete lotsizing and scheduling by batch sequencing

Article Abstract:

The discrete lotsizing and scheduling problem (DLSP) was solved as a batch sequencing problem (BSP) by determining BSP instances from DLSP instances. Item demand was represented as a job supporting a processing time and a deadline. Sequence dependent setup times and setup costs were considered for the DLSP which was characterized by several parameters. These include indexes of item and periods, holding costs, setup time and costs and item inventory. A branch-and-bound algorithm was also utilized to solve the BSP to optimality using model formulations that sequenced jobs backwards. Results showed that the DLSP can be resolved as a BSP if the problem instances are transformed. Findings also indicated that the solution effectively accommodates problems with few items and a small solution space.

Methods, Management, Production control, Economic lot size

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An exact algorithm for the Resource-Constrained Project Scheduling problem based on a new mathematical formulation

Article Abstract:

A study was conducted to analyze the Resource-Constrained Project Scheduling Problem (RCPSP) of determining the starting schedules for the activities of a project supporting precedence and resource constraints to reduce the total project time. The RCPSP supported bounds determined from a novel mathematical formulation of the problem based on 0-1 linear programming. Its formulation was characterized by a set of resources and activities with processing times. Lower bounds were obtained and correlated with relaxed problems by dropping precedence and nonpreemption constraints. Computation studies were also carried out to evaluate the performance of new lower bounds. Results indicated the competitiveness of an exact tree search procedure derived from scheduling problem.

Linear programming

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