A Coordinated Supply Chain Model for Imperfect Items under Power Function Lead Time Crashing Cost and Investment with a Service Level Constraint

This paper presents a coordinated vendor-buyer supply chain model in two stages with imperfect quality items, lead time and ordering cost reduction, and service level constraint. It is assumed that each arrival lot received by the buyer contains a percentage of imperfect quality items which follows a uniform distribution. A 100% screening process for detecting the defective items is conducted. Lead time crashing cost and investment for ordering cost reduction follow power function distribution. The shortage during the lead time is permitted and backordered partially for the buyer. However, the level of shortage is limited by service level constraint policy. The optimal order quantity, reorder point, lead time, ordering cost, and the number of delivery are determined by the Lagrange method such that joint total cost of the system is minimized and the service level constraint is satisfied. An iterative procedure is developed to determine the optimal solution and a numerical example is presented to illustrate the result of the proposed model.

Min-Max Regret Version of the Linear Time–Cost Tradeoff Problem with Multiple Milestones and Completely Ordered Jobs

We consider a linear time–cost tradeoff problem with multiple milestones and uncertain processing times such that all jobs are completely ordered. The performance measure is expressed as the sum of total weighted number of tardy jobs and total crashing cost. The processing times uncertainty is described through two types of scenarios: discrete and interval scenarios. The objective is to minimize maximum deviation from optimality over all scenarios. For the discrete scenario case, we prove its NP-hardness, develop a pseudo-polynomial time approach, and present a polynomially solvable case. Finally, we show that the interval scenario case is also NP-hard.

MULTI-OBJECTIVE TIME-COST OPTIMIZATION USING COBB-DOUGLAS PRODUCTION FUNCTION AND HYBRID GENETIC ALGORITHM

Existing research on construction time-cost tradeoff issues rarely explore the origin of the crashing cost. Crashing cost function was either assumed without much justification, or came from historical data of some real pro­jects. As a result the conclusions of the papers can hardly be used to guide allocations of labor and equipment resources respectively. The authors believe Cobb-Douglas function provides a much-needed piece to modeling the cost functions in the construction time-cost tradeoff problem during the crashing process. We believe this new perspective fills a gap of existing time-cost tradeoff research by considering project duration, labor and equipment cost as parameters of the Cobb- Douglas production function. A case study was presented to show how the proposed framework works. Our conclusion is that introducing Cobb-Douglas function into time-cost tradeoff problem provides us extra capacity to further identify the optimal allocations of labor and equipment resources during crashing.

Optimal Crashing and Buffering of Stochastic Serial Projects

Crashing stochastic activities implies changing their distributions to reduce the mean. This can involve changing the variance too. Therefore, crashing can change not only the expected duration of a project but also the necessary size of its safety buffer. We consider optimal crashing of serial projects where the objective is to minimize total costs including crashing cost and expected delay penalty. As part of the solution we determine optimal safety buffers. They allow for activities that are statistically dependent because they share an error element (e.g., when all durations have been estimated by one person, when weather or general economic conditions influence many activities, etc). We show that under plausible conditions the problem is convex and thus it can be solved by standard numerical search procedures. The purpose of the paper is to encourage software development that will include valid stochastic analysis for scheduling and crashing using current estimates and historical performance records.

Supply Chain Coordination Mechanism Based on Lead-Time Compression under Elastic Demand

The optimization for profit coordination of the supply chain under elastic demand, which involves a two-level supply chain consisted of a supplier and a buyer, is discussed. Supplier supplies in JIT mode and supply chain members reduce lead-time through lead-time crashing to reduce costs. Based on game theory and the aim of minimizing the total cost of each party respectively, a two-level stackelberg leader-follower game model, in which buyer is the leader and supplier is the follower, is established. Buyer takes all the crashing cost and gives incentives to supplier to promote cooperation. A comparison is given among the profits of buyer, supplier and system after and not after lead-time crashing respectively, and the increased benefit among the three parties after lead-time crashing is analyzed, too. Finally, a numerical example and a simulation analysis are given to show the effect of the variations of the parameters on the increased benefit of buyer, supplier and system.