In this paper, we introduce a unified mathematical formulation for the Capacitated Vehicle Routing Problem (CVRP) and for the Capacitated Location Routing Problem (CLRP), adopting radiality constraints in order to guarantee valid routes and eliminate subtours. This idea is inspired by formulations already employed in electric power distribution networks, which requires a radial topology in its operation. The results show that the proposed formulation greatly improves the convergence of the solver.

In the era of digital manufacturing and highly competitive environment, it is desirable to deliver the right item, right quantity at right time at minimal cost. Under this volatile market environment, the inventory should be readily available at the manufacturing level at the lowest possible cost. Many industries have been conventionally employing traditional ABC analyses based on a single criterion of annual consumption cost for classification of inventory items in spite of other criteria such as unit cost, consumption rate, average inventory cost that may be important in inventory classification. To address such problems, incorporation of Multi-criteria decision making (MCDM) methods is considered an advantage. The present article focuses on a new approach to categorize inventory items using Modified similarity-based method. The proposed method is applied to the inventory data of raw materials from a renowned conveyor belt manufacturing company of West Bengal, India. By using Modified similarity-based method, the items are classified in A, B and C categories. Results obtained from the said method using R program are compared with those of well recognized TOPSIS and AHP methodologies to validate the application of this method for inventory classification.

This paper presents a joint economic lot size model for a single manufacturer-a single buyer. The purposed model involves the greenhouse gas emission from industrial and transport sectors. We divide the emission into two types, namely the direct and indirect emissions. In this paper, we consider the Government’s penalty and incentive policies to reduce the emission. We assume that the demand of the buyer is normally distributed and partially backordered. The objective is to minimize joint total cost incurred by a single manufacturer-a single buyer and involves the transportation costs of the freight forwarder. Transportation costs are the function of shipping weight, distance, fuel price and consumption with two transportation modes: truckload and less-than-truckload shipments. Finally, an algorithm procedure is proposed to determine the optimal order quantity, safety factor, actual shipping weight, total emission and frequency of deliveries. Numerical examples and analyses are given to illustrate the results.

In this paper, we propose a three-phase multi-attribute ranking approach having as outcomes of the modeling phase what we refer to as net superiority and inferiority indexes. These are defined as bounded differences between the classical superiority and inferiority indexes. The suggested approach herein named MANISRA (Multi-Attribute Net Inferiority and Superiority based Ranking Approach) employs in the aggregation phase a bi-parameterized family of compound averaging operators (CAOPs) referred to as generalized Heronian OWAWA (GHROWAWA) operators having the usual OWAWA operators as special instances. Note that the new defined operators are built by using a composition of an arbitrary bi-parameterized binary Heronian mean with the weighted average (WA) and the ordered weighted averaging (OWA) operators. Also, note that the current developed MANISRA method generalizes the superiority and inferiority ranking (SIR-SAW) method which is known to coincide with the quite popular PROMETHEE II method when the net flow rule is used. With net superiority and inferiority indexes and GHROWAWA operators, we are better equipped to rank rationally prespecified alternatives. The basic formulations, notations, phases and interlocking tasks related to the proposed approach are presented herein and its feasibility and effectiveness are shown in a real problem.

Manufacturing systems need to be able to work under the dynamic and uncertain production environment. Machine and routing flexibility combined with preventive maintenance actions can improve the performance of the manufacturing systems under dynamic conditions. This paper evaluates different levels of machine and routing flexibility combined with different degrees of preventive maintenance policy. The performance measures considered are throughput, work in process and throughput. The performance measures are compared with a system without any flexibility and no preventive maintenance actions. Different levels of flexibility and preventive maintenance actions are examined under a simulation environment. The simulation results highlight more important factors for the performance measures and the best combination of the factors to improve the performance.

This study develops an empirical investigation of trust antecedents and consequences in creating a collaborative business relationship between distribution companies and retailers in the cosmetics market. A conceptual framework based on trust antecedents as inputs and trust consequences as outputs is designed for both parties. In order to evaluate the performance and effectiveness of each considered trust factor for each party, a fuzzy data envelopment analysis (FDEA) based approach is proposed. In order to demonstrate the applicability of the proposed model, a real-life case study is considered. The required data are collected using interview and questionnaires, and the reliability of the collected data is examined using the Cronbach’s alpha. The obtained results indicate that there is no significant difference between both parties’ tendency towards building a collaborative business relationship based on trust. The results also indicate that information sharing is not an effective trust antecedent for both parties. The “product quality” and “product price” are the most effective trust antecedents for retailers, while the “retailer’s financial conflicts records” along with “length of partnership” are the most effective trust antecedents for distribution companies. Finally, the most effective trust consequences for distribution companies and retailers are “information sharing” and “brand advertising”, respectively.

The aim of this study is to evaluate the impact of factors such as cutting speed, feed rate, and depth of cut on surface roughness and Material Removed Rate (MRR) when machining in dry face milling AISI 1040 steel with coated carbide inserts GC1030 using the response surface methodology (RSM). For this purpose, a number of machining experiments based on statistical three-factor and three-level factorial experiment designs, completed (L27) with a statistical analysis of variance (ANOVA), were performed in order to develop mathematical models and to identify the significant factors of these technological parameters. Multi-objective optimization procedure for minimizing Ra, Ry and Rz and maximizing MRR using desirability approach has been also implementented. The current study was also carried out to investigate the tool life of the inserts. The models found the relationship between the cutting parameters (Vc, fz and ap) and the studied technological parameters. It has been found that the cutting speed was the most affecting surface roughness which is due to the geometry of the insert which has a scraping edge and enables to obtain low roughness even at important feed rate, followed by the feed rate and the depth of cut at the end. The optimal combination of cutting parameters were cutting speed of 314 m/min, feed rate of 0.16 mm/tooth and depth of cut of 0.6 mm with a composite desirability of 0.924.

Closed-loop supply chain management is an effective and efficient solution for a set of activities to retrieve a product from a customer and improve its value or to dispose it. Today, designing and planning a closed-loop chain is an inevitable but difficult task. In this research, a scenario-based modeling approach is presented by considering both forward and reverse flows as a closed-loop supply chains in steel industry. The proposed study also develops a multi-product and multi-period model based on a mixed integer linear programming (MILP) approach for profit maximization. The study also considers uncertainty in the amount of raw material, processing, storage and distribution of several products flow. Uncertainty is associated with the quantity and quality of the products in the reverse flow, which are directly affected by customers and sorting centers, respectively. Finally, the model is deployed in Steel industry with real data. The results show that by increasing the quality level of returned products the need for raw materials is reduced and the total profit of the supply chain is increased.

This paper proposes a two-phase heuristic algorithm to solve the crew scheduling problem of the Megabus Bus Rapid Transit System. In the first stage, a division of the original schedules is performed using a recursive algorithm based on dynamic scheduling. In the second stage, work-shift construction based on graph theory is performed using a pairing algorithm (i.e., matching). The method is validated by applying it to the mass transit system of the Central Western Metropolitan Area (AMCO), operated by Integra SA, which serves 11 routes for a daily total of 2899 trips.

In production/inventory control systems, the goal of the controller is to generate sophisticated decisions by controlling the order rate and inventory level. This paper aims at modeling a dynamic-stochastic production/inventory control system under two sources of variability (uncertainty) including uncertainties on demand rate and frustrating rate. The study deals with obtaining a robust optimal design of a Proportional-Integral-Derivative (PID) controller in in the stochastic control system. For this purpose, a new robust simulation-optimization method in the class of computational intelligence is proposed. To cope with the unknown distribution of uncertainty, the crossing weighted uncertainty scenarios are combined with the proposed method. Within this study, a new sequential robust efficient global optimization is proposed to make a trade-off between optimal and robustness terms in final optimization results. Finally, a numerical case with simulation experiments is conducted to demonstrate the advantages of the proposed policy in terms of optimal result, robustness, and computational cost.