Capital flow constrained lot sizing problem with loss of goodwill and loan

TL;DR

This paper introduces a novel lot sizing model incorporating capital flow constraints, goodwill loss, and loans, providing an efficient algorithm that outperforms traditional methods in large-scale deterministic single-item problems.

Contribution

It develops a mixed integer model with a new approach approximating it to a traveling salesman problem, and proposes a recursive heuristic algorithm for efficient solutions.

Findings

The algorithm achieves optimal solutions in specific cases with zero goodwill loss.

Numerical results show the algorithm is effective and faster than CPLEX for large problems.

Initial capital and loan interest significantly influence lot sizing decisions.

Abstract

We introduce capital flow constraints, loss of good will and loan to the lot sizing problem. Capital flow constraint is different from traditional capacity constraints: when a manufacturer launches production, its present capital should not be less than its present total production cost; otherwise, it must decrease production quantity or suspend production. Unsatisfied demand in one period may cause customer's demand to shrink in the next period considering loss of goodwill. Fixed loan can be adopted in the starting period for production. A mixed integer model for a deterministic single-item problem is constructed. Based on the analysis about the structure of optimal solutions, we approximate it to a traveling salesman problem, and divide it into sub-linear programming problems without integer variables. A forward recursive algorithm with heuristic adjustments is proposed to solve it. When unit variable production costs are equal and goodwill loss rate is zero, the algorithm can obtain optimal solutions. Under other situations, numerical comparisons with CPLEX 12.6.2 show our algorithm can reach optimal in most cases and has computation time advantage for large-size problems. Numerical tests also demonstrate that initial capital availability as well as loan interest rate can substantially affect the manufacturer's optimal lot sizing decisions.