Revenue optimization based on price, delivery time, andcapacity

The intention of this thesis investigate the optimum price, guaranteed delivery time, and capacity expansion level of a single firm to maximize its profit per time in the make-to-order system under a deterministic environment. A log-linear demand model that depends on the sales price and guaranteed delivery time of a single product is used. In order to satisfy customer demand, guaranteed delivery time must be met at a certain service level. The firm has the option to expand its production capacity at a cost in order to meet demand and satisfy predefined service level by delivering the product within a guaranteed delivery time. A mathematical programming model for profit maximization is constructed to observe the relation between these three decision variables; price, guaranteed delivery time, and capacity expansion level, and find the optimal decision variables set that maximize the profit. The characteristics of decision variables are investigated for different frameworks and parameters. Our model complements the literature as we introduce convex exponential capacity expansion function alongside the linear capacity expansion cost function. Additionally, we consider production cost as a decreasing function of guaranteed delivery time. We perform a computational study to find the optimal solution set and make observations regarding these results. We further provide general managerial insights about which strategies should be adapted according to company structure.