Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems

Strategic and operational decisions in supply chains

In this work, we develop models that supply chains can employ to satisfy periodic and stochastic demand effectively. These models combine the strategic and operational decisions to cost function. Strategic decisions are represented by the size of capacity acquired, while operational decisions are represented by the parameters of the inventory policy employed.;In addition to combining the strategic and operational decisions, the developed models study three alternatives that can reduce the cost of satisfying the demand by relying on external production to outsource or subcontract some of the demand. Outsourcing is studied where a fixed amount of the product is delivered to the supply chain each time period regardless of the demand and inventory status.;Subcontracting is employed if the inventory status reaches a certain level that justifies going to a third party. Collaboration is the last alternative considered where two supply chains cooperate to satisfy the demand they are subject to. Two models of collaboration are studied; in the first model, collaboration takes place by exchanging unused capacity while in the second model, collaboration happens by exchanging finished products.;A simple stochastic approximation method is used to find the optimum parameters that minimize the cost functions considered. The costs are evaluated using simulation, while the gradient of the cost with respect to the different parameters is found using infinitesimal perturbation analysis (IPA). The validity of the suggested optimization method is checked graphically for models having three parameters to optimize.;Different experiments are conducted to study the response of the supply chain to its working environment and parameters for both single stage supply chains and multi-echelon supply chains. The working environment; is changed, by changing the variability of the demand that the supply chain is trying to satisfy and by changing the cost of the units satisfied from external sources. Holding cost, capacity cost and backordering cost are the supply chain parameters changed in these studies

The Multi-Location Transshipment Problem with Positive Replenishment Lead Times

Transshipments, monitored movements of material at the same echelon of a supply chain, represent an effective pooling mechanism. With a single exception, research on transshipments overlooks replenishment lead times. The only approach for two-location inventory systems with non-negligible lead times could not be generalized to a multi-location setting, and the proposed heuristic method cannot guarantee to provide optimal solutions. This paper uses simulation optimization by combining an LP/network flow formulation with infinitesimal perturbation analysis to examine the multi-location transshipment problem with positive replenishment lead times, and demonstrates the computation of the optimal base stock quantities through sample path optimization. From a methodological perspective, this paper deploys an elegant duality-based gradient computation method to improve computational efficiency. In test problems, our algorithm was also able to achieve better objective values than an existing algorithm.Transshipment;Infinitesimal Perturbation Analysis (IPA);Simulation Optimization

A comprehensive literature classification of simulation optimisation methods

Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measureSimulation Optimization, classification methods, literature survey

An optimal-control based integrated model of supply chain

Problems of supply chain scheduling are challenged by high complexity, combination of continuous and discrete processes, integrated production and transportation operations as well as dynamics and resulting requirements for adaptability and stability analysis. A possibility to address the above-named issues opens modern control theory and optimal program control in particular. Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of complexity, dynamics, uncertainty, and adaptivity. Supply chain schedule generation is represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. The calculation procedure is based on applying Pontryagin’s maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. With the developed model, important categories of supply chain analysis such as stability and adaptability can be taken into consideration. Besides, the dimensionality of operations research-based problems can be relieved with the help of distributing model elements between an operations research (static aspects) and a control (dynamic aspects) model. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes.supply chain, model of supply chain scheduling, optimal program control theory, Pontryagin’s maximum principle, operations research model,

Ensemble Differential Evolution with Simulation-Based Hybridization and Self-Adaptation for Inventory Management Under Uncertainty

This study proposes an Ensemble Differential Evolution with Simula-tion-Based Hybridization and Self-Adaptation (EDESH-SA) approach for inven-tory management (IM) under uncertainty. In this study, DE with multiple runs is combined with a simulation-based hybridization method that includes a self-adaptive mechanism that dynamically alters mutation and crossover rates based on the success or failure of each iteration. Due to its adaptability, the algorithm is able to handle the complexity and uncertainty present in IM. Utilizing Monte Carlo Simulation (MCS), the continuous review (CR) inventory strategy is ex-amined while accounting for stochasticity and various demand scenarios. This simulation-based approach enables a realistic assessment of the proposed algo-rithm's applicability in resolving the challenges faced by IM in practical settings. The empirical findings demonstrate the potential of the proposed method to im-prove the financial performance of IM and optimize large search spaces. The study makes use of performance testing with the Ackley function and Sensitivity Analysis with Perturbations to investigate how changes in variables affect the objective value. This analysis provides valuable insights into the behavior and robustness of the algorithm.Comment: 15 pages, 6 figures, AsiaSIM 2023 (Springer

The Multi-Location Transshipment Problem with Positive Replenishment Lead Times

Transshipments, monitored movements of material at the same echelon of a supply chain, represent an effective pooling mechanism. With a single exception, research on transshipments overlooks replenishment lead times. The only approach for two-location inventory systems with non-negligible lead times could not be generalized to a multi-location setting, and the proposed heuristic method cannot guarantee to provide optimal solutions. This paper uses simulation optimization by combining an LP/network flow formulation with infinitesimal perturbation analysis to examine the multi-location transshipment problem with positive replenishment lead times, and demonstrates the computation of the optimal base stock quantities through sample path optimization. From a methodological perspective, this paper deploys an elegant duality-based gradient computation method to improve computational efficiency. In test problems, our algorithm was also able to achieve better objective values than an existing algorithm

Econometric Estimation of Parameters of Preservation of Perishable Goods in Cold Logistic Chains

Paper discusses the parameters of preservation of perishable goods in cold logistic chains. The key parameters are the intensity of deterioration of goods, the conservation effect of perishable goods and the delay of activation of the conservation effect. The values of these parameters tell us the quantity of the product being deteriorated in the logistic chain and the extent to which the deterioration can be alleviated. Econometric estimation thus presents us with the quantity effects of preservation procedures, whereas the financial effects can be derived using the proper price categories in the calculation of the net present value or the annuity stream. In this way one can determine whether the implementation of preservation procedures is more rational than the purchase of attainable insurance policy.cold chains, Cold Chains Management, econometric estimation, intensity of deterioration, conservation effect, Input – Output analysis, Laplace transforms, MRP