Common Cycle Time Research Articles

Green Wave Control Model Simultaneously Considering Passenger Cars and Buses in Closed Road Networks

Existing green wave control methods for passenger cars and buses mainly focus on maximizing bandwidths at the arterial level. There is little research on green wave control for both at the closed road network level, which makes it difficult to improve the efficiency of the entire area. To address this, a green wave control model that considers both passenger cars and buses in closed road networks is presented in this paper. The objective function of the model is to maximize the sum of the weighted bandwidths of passenger cars and buses on each segment of the road network. The relationships between car green bands, bus green bands, offsets, phase sequences, red time, green time, etc. are analyzed on the level of arterials and road networks, respectively, using time–space diagrams. Based on these analyses, the key constraints of the model are constructed accordingly. In addition, 0/1 variables and a sufficiently large positive number M are introduced to relax some of the constraints to ensure that the presented model has feasible solutions. The results of the numerical example demonstrate that compared with the fixed phase sequence schemes 1, 2, and 3, the total weighted bandwidth generated by the presented model increased by 9.5%, 16.4%, and 17%, respectively. Compared with the model without constraint relaxation, the presented model can still find a global, optimal solution when the common cycle time is fixed, while the model without constraint relaxation has no feasible solution.

A Cooperative Agent-Based Traffic Signal Control for Vehicular Networks Under Stochastic Flow

A two-tier Cooperative Agent-based Traffic Signal control (CATS) is proposed to minimize total delay for independent-learning signal-controlled junctions. For vehicular networks with traffic congestion, a link traffic model is presented to estimate time-varying signal delay under stochastic travel demand. To capture essential features of signal-controlled junctions, an agent-based value function approximator is proposed. For the 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> tier, common cycle time and offsets are explored to achieve collaboration among control agents. For the 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> tier, green splits are exploited to ensure scalability over entire vehicular networks. A stochastic bi-level program is presented to minimize total delays. Numerical experiments are performed at a real-data vehicular network under stochastic flow. Comparisons are made with state-of-the-art traffic signal controls. As reported, the proposed CATS outperforms other alternatives in all cases.

Commissioning and performance of TITAN’s Multiple-Reflection Time-of-Flight Mass-Spectrometer and isobar separator

TRIUMF’s Ion Trap for Atomic and Nuclear science (TITAN) has specialized in fast Penning Trap mass spectrometry of very short-lived radioactive isotopes. The facility has been upgraded with a Multiple-Reflection Time-of-Flight Mass Spectrometer (MR-TOF-MS) to continue its quest towards more exotic nuclides, which are critical for our understanding of nuclear structure effects far from the valley of beta stability and for the nucleosynthesis of heavy elements in explosive astrophysical environments. In this publication, we discuss the implementation, operation and performance of TITAN’s MR-TOF-MS as a stand-alone high-precision mass spectrometer and as an isobar separator. By using the novel mass-selective re-trapping technique for the isobar separation, the MR-TOF-MS can consecutively perform separation and mass measurement of the same ion population, acting as its own isobar separator. The device boosts the dynamic range and reach of the TITAN facility by several orders of magnitude. The MR-TOF-MS reaches a high mass resolving power (m/Δm∼400000), high precision and mass accuracy (δm/m<10−7), is fast (common cycle time 20ms), shows high sensitivity and very large dynamic range (ion of interest to contaminant ratios of up to 1 to 106).

Incorporating Outsourcing Strategy and Quality Assurance into a Multiproduct Manufacturer–Retailer Coordination Replenishing Decision

This study explores the multiproduct manufacturer-retailer coordination replenishing decision featuring outsourcing strategy and product quality assurance. Globalization has generated enormous opportunities. Consequently, transnational firms now face tough competition in global markets. To stay competitive, a firm should meet the client’s multi-item and quality requirements under capacity constraints and optimize the intra-supply chain system to allow the timely distribution of finished goods under minimum system cost. The outsourcing option is considered to release machine loadings and reduce cycle time effectively. All items fabricated are screened for quality, and reworkable and scrap items are separated. Any reworked items that fail the quality reassurance screening are discarded, whereas all outsourced products are quality-guaranteed by the provider. A fixed-quantity multi-shipment plan is used when the whole finished lot is quality-ensured to help present-day transnational firms gain competitive advantage by making efficient and cost-effective multiproduct manufacturing and delivering decisions. Mathematical modeling is built to portray the system’s characteristics, and conventional differential calculus is used to solve and derive the optimal operating policy for the proposed problem. Simultaneously, we find the optimal delivery frequency and common cycle time for the problem mentioned above. A simulated numerical example and sensitivity analysis demonstrate the research result’s capability and applicability. Our precise analytical model can reveal/highlight the impact of deviations in quality- and outsourcing-related features on the optimal operating policy and several performance indicators that help managerial decision-making.

An Algebraic Decision Support Model for Inventory Coordination in the Generalized n-Stage Non-Serial Supply Chain with Fixed and Linear Backorders Costs

This paper extends and generalizes former inventory models that apply algebraic methods to derive optimal supply chain inventory decisions. In particular this paper considers the problem of coordinating production-inventory decisions in an integrated n-stage supply chain system with linear and fixed backorder costs. This supply chain system assumes information symmetry which implies that all partners share their operational information. First, a mathematical model for the supply chain system total cost is formulated under the integer multipliers coordination mechanism. Then, a recursive algebraic algorithm to derive the optimal inventory replenishment decisions is developed. The applicability of the proposed algorithm is demonstrated using two different numerical examples. Results from the numerical examples indicate that adopting the integer multiplier mechanism will reduce the overall total system cost as compared to using the common cycle time mechanism.

Periodic review integrated inventory model with controllable lead time and setup cost in the presence of a service level constraint

The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service level constraints is explored in this study. Distribution free and normal distribution procedure with Lagrange multipliers is applied to determining the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimised. The efficient algorithm is constructed to find the optimal lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle simultaneously. Moreover, the numerical example is introduced to illustrate the proposed model. Through sensitivity analysis, some observations and managerial implications are provided.

A new mathematical model for production and delivery scheduling problem with common cycle in a supply chain with open-shop system

In order to coordinate the supply chain, reordering strategy of needed goods must be synchronised and sequence of production and replenishment cycle time must be optimised in terms of cost. Therefore, this paper studies the economic lot and delivery scheduling problem for multi-stage supply chain. The common cycle time and integer multiplier policies were adopted to accomplish the desired synchronisation. In this regard, a new mathematical model has been presented where a manufacturer with open-shop system purchases raw materials from suppliers and sends them to packaging companies after converting them into the final product and then they are sold. Since this is a non-deterministic polynomial-time hard (NP-hard) problem, simulated annealing algorithms have been developed for it. For this algorithm, two different scenarios have been proposed for solving the study problem and at the end the numerical results have been applied on problems with different dimensions by the algorithm.

Meeting multiproduct demand with a hybrid inventory replenishment system featuring quality reassurance

Globalization has not only generated immense business opportunities, but also created a very competitive marketplace. To retain competitive advantage, a manufacturer must satisfy a client's multiproduct and quality requirements with limited in-house capacity. An outsourcing strategy can overcome capacity constraints and shorten the fabrication cycle time. This study explores a hybrid multiproduct single-machine inventory replenishment system incorporating an outsourcing plan. The in-house multiproduct fabrication process is under a common cycle time policy. That is, each product receives one replenishment in a common cycle length. All fabricated items are inspected for quality; items with random defects are sorted out as scrap and repairable, and the rework occurs immediately after the regular fabrication. All reworked products that fail the quality reassurance test are scrapped. The quality of outsourcing items is assumed to be guaranteed by the outside provider. Our objective is to determine the optimal common cycle time that minimizes the total relevant cost. An accurate model is constructed to represent the characteristics of the system studied; furthermore, we utilize mathematical analysis to derive the total system costs and apply differential calculus to find the optimal cycle length. A numerical example illustrates the applicability of our result and highlights the effect of variations in outsourcing- and quality-related attributes on the optimal solution, as well as the various performance indicators that facilitate planning and controlling decisions.

Coordination Control for an Arterial Bus Based on the Ring-Barrier Phase

Coordination control is implemented on the main public transport system to reduce delay and improve the operation efficiency of buses on urban arterial roadways. First, the concept of a dual-loop phase is introduced and a new phase structure and sequences are proposed. Then, optimization models of the common signal cycle and effective green light time are built. Second, a genetic algorithm is used to optimize signal offset in coordination control according to the driving characteristics of a bus. To evaluate the effect of coordination control, a delay function is established to describe the control effect according to theory of triangle delay. Finally, the main arterial road is selected for a case study. The main parameters, such as common signal cycle, effective green light time, and offset, are optimized using Lingo and MATLAB. Results show that the bus delay value tends to decline after implementing the algorithm and the 50th iterative optimization result is 20.13% lower than that of the first iteration.

Coordination policy for production and delivery scheduling in the closed loop supply chain

Coordinating a supply chain necessitates a synchronization strategy for reordering products and a cost-effective production and replenishment cycle time. The aim of this paper is to present an optimization framework for producing and distribution in the supply chains with a cooperating strategy. The main contribution of this paper is to integrate closed loop supply chain with open-shop manufacturing and economic lot and delivery scheduling problem (ELDSP). This integration is applied with the aim of better coordination between the members of the supply chain. This study examines the ELDSP for a multi-stage closed loop supply chain, where each product is returned to a manufacturing center at a constant rate of demand. The supply chain is also characterized by a sub-open-shop system for remanufacturing returned items. Common cycle time and multiplier policies is adopted to accomplish the desired synchronization. For this purpose, we developed a mathematical model in which a manufacturer with an open-shop system purchases raw materials from suppliers, converts them into final products, and sends them to package companies. Given that the ELDSPR is an NP-hard problem, a simulated annealing (SA) algorithm and a biography-based optimization (BBO) algorithm is developed. Two operational scenarios are formulated for the simulated annealing algorithm, after which both the algorithms are used to solve problems of different scales. The numerical results show that the biography-based optimization algorithm excellently performs in finding the best solution to the ELDSPR.

Offset optimization in signalized traffic networks via semidefinite relaxation

We study the problem of selecting offsets of the traffic signals in a network of signalized intersections to reduce queues of vehicles at all intersections. The signals in the network have a common cycle time and a fixed timing plan. It is assumed that the exogenous demands are constant or periodic with the same period as the cycle time and the intersections are under-saturated. The resulting queuing processes are periodic. These periodic processes are approximated by sinusoids. The sinusoidal approximation leads to an analytical expression of the queue lengths at every intersection as a function of the demands and the vector of offsets. The optimum offset vector is the solution of a quadratically constrained quadratic program (QCQP), which is solved via its convex semidefinite relaxation. Unlike existing techniques, our approach accommodates networks with arbitrary topology and scales well with network size. We illustrate the result in two case studies. The first is an academic example previously proposed in the literature, and the second case study consists of an arterial corridor network in Arcadia, California.

A hybrid imperialist competitive algorithm for solving economic lot and delivery scheduling problem in a four-stage supply chain

In this article, we study the economic lot and delivery scheduling problem for a four-stage supply chain that includes suppliers, fabricators, assemblers, and retailers. All of the parameters such as demand rate are deterministic and production setup times are sequence-dependent. The common cycle time and integer multipliers policies are adapted as replenishment policies for synchronization throughout the supply chain. A new mixed integer nonlinear programming model is developed for both policies, the objective of which is the minimization of inventory, transportation, and production setup costs. We propose a new hybrid algorithm including a modified imperialist competitive algorithm which is purposed to the assimilation policy of imperialist competitive algorithm and teaching learning–based optimization which is added to improve local search. A hybrid modified imperialist competitive algorithm and teaching learning–based optimization is applied to find a near-optimum solution of mixed integer nonlinear programming in large-sized problems. The results denoted that our proposed algorithm can solve different size of problem in reasonable time. This procedure showed its efficiency in medium- and large-sized problems as compared to imperialist competitive algorithm, modified imperialist competitive algorithm, and other methods reported in the literature.

Cost Minimization for a Multi-Product Fabrication-Distribution Problem with Commonality, Postponement, and Quality Assurance

To gain more competitive advantages and attract more customers from the turbulent business environment, manufacturing firms today must offer a wide variety of products to marketplaces. The existence of component commonality in multi-product fabrication planning enables managers to reevaluate different production design alternatives to lower overall production relevant costs. Motivated by assisting managers of manufacturing firms in gaining competitive advantages, maximizing machine utilization, and reducing overall quality and fabrication-distribution costs, this study explores a multi-product fabrication-distribution problem with component commonality, postponement, and quality assurance. A two-stage single-machine production scheme with the reworking of repairable nonconforming items is proposed. The first stage fabricates common intermediate components for all products, and the second stage produces and distributes end products under a common cycle time policy. Mathematical modeling and optimization techniques are utilized to derive the optimal fabrication-distribution policy that minimizes the expected total system costs of the problem. Finally, we provide a numerical example with sensitivity analyses to not only show practical uses of the obtained results, but also demonstrate that the proposed production scheme is beneficial in terms of cost savings and cycle time reduction as compared to that in a single-stage production scheme. The research results enable manufacturers to gain more competitive advantages in the turbulent global business environment.

Determination of optimal order-up to level quantities for dependent spare parts using data mining

Consumable spare parts play an important role during regular and periodic maintenance activities depending on equipment criticality of a manufacturing firm. Usually, these spare parts are consumed together on a regular basis to different equipment with a high percentage of commonality. Complete or partial shutdown of maintenance activity may happen if there is shortages in any of these common parts and at the same time, maintaining a high inventory of these parts lead to more cost. If there is a shortage of a spare part, then there is a chance that other dependent spares may remain as idle inventory and incur the opportunity cost. In this paper, a noble approach is adopted to incorporate dependency of items in periodic review (T, S) policy to determine the optimal stock of dependent spare parts considering common cycle time and fill rate for each spares. Our results show that there is considerable reduction of stock level and total cost of inventory when associated spares are considered together for management of inventory instead of considering them individually. Finally, the developed model is applied to a case company.

A simplified approach to the multi-item economic production quantity model with scrap, rework, and multi-delivery

In a recent paper, Chiu et al. (2014) utilized mathematical modeling and differential calculus to determine the common production cycle time that minimizes total production, inventory, and delivery costs for a multi-item economic production quantity (EPQ) model with scrap, rework, and multi-delivery. The present study proposes an algebraic approach substituting the use of differential calculus on the system cost function for deriving the optimal common cycle time in the aforementioned multi-item EPQ model. This simplified approach may enable managing practitioners to resolve real multi-item EPQ models more effectively. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.

On the range of the common cycle time in a road network

In a coordinated road network, the optimal common cycle time is determined by evaluating the performance of the network in the given range of cycles. Normally, this range is determined by users’ experience. And a large range of common cycle times, e.g. [30, 200] is chosen, which requires long computation time. This study considers that the optimal common cycle time ranges between the minimal and maximal value of intersections’ individual optimal cycle time. It is proved mathematically from the convexity condition, that the delay of the network and each individual intersection are convex functions of the cycle time according to Webster delay model. Finally, 2000 random cases for the network composed of two intersections and of eight intersections are created to underline the proposed conclusions. The results of all cases confirm the validity, and show up to 90% improvement in computation time to compare with experience range. The signal optimization tool, Synchro, is also used to validate the conclusion by 50 random cases. The results confirm reliability further.

Optimization of a multi-product EPQ model with scrap and an improved multi-delivery policy

This paper considers optimization of a multi-product economic production quantity(EPQ) model with scrap items and an improved multi-delivery policy. We extend thework of Chiu et al. (2013a) by incorporating an improved n + 1 multi-delivery planinto their model with an aim at reducing vendor’s inventory holding cost. Under such aspecific shipment policy, for each product an extra delivery of finished goods is madeduring production uptime to satisfy the product demand for the period of vendor’suptime. Then, when rework process comes to an end (i.e., the rest of the productionlot is quality assured) n fixed quantity installments of finished goods are delivered tobuyers at a fixed time interval. The objectives of this study are to determine the optimalrotation production cycle time that minimizes the long-run average system cost perunit time and reveals the effects of random scrap rate and the improved delivery policyon the optimal production cycle time. With the help of a mathematical model a closedformoptimal common cycle time is derived. Through a numerical example, practicalusages of obtained results and significant savings in vendor’s stock holding cost aredemonstrated.

Comparison of the Effectiveness of Common Cycle Computing Models

In a coordinated road network, the common cycle is selected by evaluating the performance of the network in the given cycle length range. There are some models to compute the common cycle length. This study give a review of these current models which are TRANSYT, Synchro, “90% rule” and “largest rule”. This paper proposes a comparing model by using the Webster delay model as well. The network composed of 4 intersections is used to test the effectiveness of these five models. 15 volume levels for the main street from 250 vehicles/hour to 750 vehicles/hour are estimated. The simulation of all common cycles by all models at all volume levels are conducted by four simulation tools which are TRANSYT-14, Synchro-7, SUMO and Simtraffic. The conclusions of the effectiveness of these models are drawn through amount of experiments. It can’t say simply that which model is the best and which is the second best and so on, because MOEs at different volume levels are different. Overall, TRANSYT and “90% rule” have better MOEs at most volume levels, while the common cycle time calculated by “90% rule” is too short. The effectiveness of comparison model in this paper is not as good as commercial program, but the difference is small.

Multi-Item EPQ Model with Scrap, Rework and Multi-Delivery using Common Cycle Policy

This paper is concerned with determining the optimal common production cycle policy for a multi-item economicproduction quantity (EPQ) model with scrap, rework and multiple deliveries. The classic EPQ model considers theoptimal replenishment quantity of single product under a perfect production assumption and a continuous inventoryissuing policy. However, in real life production planning, manufacturing firms often plan to have multiple productsmade in turn on a single machine in order to maximize the machine utilization. Also, dealing with random defectiveitems during the production run seems to be an inevitable task, and the multi-delivery policy is commonly adopted fordistributing finished items to customers. In this study, we assume a portion of nonconforming items is scrap and theother portion of them can be reworked and repaired in the same production cycle with additional cost. The objective isto determine an optimal common production cycle time that minimizes the long-run average cost per unit time for sucha specific multi-item EPQ model with scrap, rework and multi-delivery policy. Mathematical modeling and analysis isused and a closed-form optimal common cycle time for multi-item production planning is obtained. A numericalexample is provided to demonstrate the practical usage of research result.

Alternative approach to determine the common cycle time for a multi-item production system with discontinuous deliveries and failure in rework

This study employs an alternative approach to determine common production cycle time for a multi-item production system with discontinuous deliveries and failure in rework. A straightforward approach using algebraic derivation is proposed here to reexamine a specific common cycle time problem studied by Chiu et al. (2013a,b), where they used the conventional method with the need of applying first-order and second-order differentiations to system cost function for proof of convexity before deriving the optimal common cycle time. The result of this study is confirmed to be identical to that was obtained in Chiu et al. (2013a,b). This alternative approach enables practitioners who may not have sufficient knowledge of differential calculus to manage the real-life multi-item production systems more effectively.