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The problems of urban distribution and the need to confront them particularly at a time of escalating petrol costs, is one of the most urgent issues facing retailers and food suppliers today. Hence the conference held recently, organised by the National Materials Handling Centre, and entitled ‘Urban distribution — strategy for the future’. One of the major preoccupations was the conflict of interests which impedes progress; environmental lobbies, central and local planning, EEC legislation. However, this paper by Alan Rushton buries these differences beneath his overriding concern with the practical rather than the ideological aspect of the subject. His point of reference is a study which looked into the problems of high street delivery, producing a scale of importance for the various difficulties encountered, and assessing the likely success of the solutions available.

In the modern era of e-grocery, attended home delivery (AHD) has been identified as a crucial part of the last-mile delivery problem. This paper aims to deal with a real-life last-mile-delivery problem in the context of the Indian public distribution system (PDS). The authors identified two different environments for the said AHD problem and proposed two different approaches to address the issue under these problem settings.

In this study, the authors first consider the problem in a static environment and propose an iterated local search (ILS) integrated with an adaptive large neighborhood search (ALNS) meta-heuristic algorithm to obtain a routing solution. Thereafter, they extend the study in a dynamic environment where new delivery requests occur dynamically and propose a heuristic algorithm to solve the problem. For the dynamic case, multiple scenarios for the occurrence of delivery requests are considered to determine decisions regarding the opportunity to include a new request into the current solution.

By computational experiments, the authors show that the proposed approach performs significantly well for large size problem instances. They demonstrate the differences and advantages of the dynamic problem setting through a set of different scenarios. Also, they present a comparative analysis to show the benefits of adopting the algorithm in dynamic routing scenarios.

Future research may extend the scope of this study by incorporating stochastic delivery failure probabilities and customer behavior affecting the delivery response. Also, the present study does not take inventory policies at the depot into consideration. It will be of interest to see how the system performs under the uncertainty of supply from the depot. Despite the limitations, the authors believe that this study provides food for thought and encouragements for practitioners.

This study shows the benefits of adopting an AHD problem in a dynamic setting in terms of customer service as compared to a traditional static environment. The authors clearly demonstrate the differences and advantages of the dynamic problem setting through a set of different scenario analysis.

This paper investigates a real-life AHD problem faced by the Department of Food, Supply and Consumer Affairs, India. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India.

The study is unique and highly relevant for real-world applications and can help build a more robust AHD system. Also, the proposed solution approaches to aid the problem in both static and dynamic routing scenarios will be of particular interest to practitioners.

Being the final end of the logistic distribution, attended home delivery (AHD) plays an important role in the distribution network. AHD typically refers to the service provided by the distribution service provider to the recipient's doorstep. Researchers have always identified AHD as a bottleneck for last-mile delivery. This paper addresses a real-life stochastic multi-objective AHD problem in the context of the Indian public distribution system (PDS).

Two multi-objective models are proposed. Initially, the problem is formulated in a deterministic environment, and later on, it is extended to a multi-objective AHD model with stochastic travel and response time. This stochastic AHD model is used to extensively analyze the impact of stochastic travel time and customer response time on the total expected cost and time-window violation. Due to the NP-hard nature of the problem, an ant colony optimization (ACO) algorithm, tuned via response surface methodology (RSM), is proposed to solve the problem.

Experimental results show that a change in travel time and response time does not significantly alter the service level of an AHD problem. However, it is strongly correlated with the planning horizon and an increase in the planning horizon reduces the time-window violation drastically. It is also observed that a relatively longer planning horizon has a lower expected cost per delivery associated.

The paper does not consider the uncertainty of supply from the warehouse. Also, stochastic delivery failure probabilities and randomness in customer behavior have not been taken into consideration in this study.

In this paper, the role of uncertainty in an AHD problem is extensively studied through a case of the Indian PDS. The paper analyzes the role of uncertain travel time and response time over different planning horizons in an AHD system. Further, the impact of the delivery planning horizon, travel time and response time on the overall cost and service level of an AHD system is also investigated.

This paper investigates a unique and practical AHD problem in the context of Indian PDS. In the present context of AHD, this study is highly relevant for real-world applications and can help build a more efficient delivery system. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India.

The most challenging part of an AHD problem is the requirement of the presence of customers during the time of delivery, due to which the probability of failed delivery drastically increases if the delivery deviates from the customer's preferred time slot. The paper modelled an AHD system to incorporate uncertainties to attain higher overall performance and explore the role of uncertainty in travel and response time with respect to the planning horizon in an AHD, which has not been considered by any other literature.

The role of business logistics for a water distribution company in Central Asia has become a major concern. As the marketing environment is getting more and more competitive, the company is forced to focus on the efficiency of its supply chain management operations both by improving customer service, increasing its profitability and productivity. The purpose of this paper is to report upon the designing of a responsive supply chain for water distribution in Central Asia.

A logistic plan to satisfy customer requirement for water distribution in a Central Asian city subject to satisfactory service levels both in the number of distribution centers (DCs) and truck delivery schedule is outlined in this paper. The logistics plan includes repositioning the DCs in relation to the customer location for efficient distribution. The problem is formulated as truck delivery schedule using a new algorithm where single distribution centre is converted into a multiple warehouse location problem. The problem is solved using WINQSB software. Further, the current DCs are appraised with the software and suggested possible new locations for convenience.

The application part of this case study consists of identifying water DCs in city limits. By developing improved distribution and logistics management, the study aims at economical operations, convenient zonal distributions, and responsive SCM characteristics. To this end, a spatial distribution plan and route sequencing solution is developed for water distribution.

The paper shows how to improve logistic network that results in cost savings, convenient zonal distributions, and responsive SCM operations. To this end, a spatial distribution plan and route sequencing is developed for water distribution.

The Fred Meyer Charitable Trust, Division of Library and Information Resources for the Northwest, has funded five research projects that will demonstrate the potential of various techniques and new technologies to facilitate communications and resource sharing in the Northwest. The experience and information derived from these projects will be of value to all libraries and information centers, not just those conducting the research. The techniques and technologies being evaluated include: simultaneous remote searching, which uses inexpensive terminals and modems; a mini‐computer‐based union list and resource sharing network (INFONET); networks using facsimile machines; networks that transmit documents that have been optically scanned into bit‐map image files; and use of optical character recognition equipment to capture ASCII machine‐readable information that can be broadcast by television stations to user‐sites. Contributors of reports are: Verl Anderson, Linda Brander, Millard F. Johnson, Jr., Bruce Morton, and Steve Smith. Summary observations are provided by Joseph R. Matthews.

This paper aims to investigate the scheduling and loading problems of tow trains for mixed-model assembly lines (MMALs). An in-plant milk-run delivery model has been formulated to minimize total line-side inventory for all stations over the planning horizon by specifying the departure time, parts quantity of each delivery and the destination station.

An immune clonal selection algorithm (ICSA) combined with neighborhood search (NS) and simulated annealing (SA) operators, which is called the NSICSA algorithm, is developed, possessing the global search ability of ICSA, the ability of SA for escaping local optimum and the deep search ability of NS to get better solutions.

The modifications have overcome the deficiency of insufficient local search and deepened the search depth of the original metaheuristic. Meanwhile, good approximate solutions are obtained in small-, medium- and large-scale instances. Furthermore, inventory peaks are in control according to computational results, proving the effectiveness of the mathematical model.

This study works out only if there is no breakdown of tow trains. The current work contributes to the in-plant milk-run delivery scheduling for MMALs, and it can be modified to deal with similar part feeding problems.

The capacity limit of line-side inventory for workstations as well as no stock-outs rules are taken into account, and the scheduling and loading problems are solved satisfactorily for the part distribution of MMALs.

The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

Key components of the logistics mix are described in an effort to create an understanding of the total logistics concept. Chapters include an introduction to logistics; the strategic role of logistics, customer service levels, channel relationships, facilities location, transport, inventory management, materials handling, interface with production, purchasing and materials management, estimating demand, order processing, systems performance, leadership and team building, business resource management.

The study aims to explore and develop a smart route planning system for the cross-docking delivery operations of a large supermarket chain using an action research (AR) approach and assessing through a design science research (DSR) lens.

This study took a problem-solving AR (PAR) approach toward the delivery operational issue of the case firm. The research process has accorded with the solution incubation and the refinement phases defined by a DSR framework. An intervention-based research framework for DSR is developed to assess the validity of this study as a DSR research and derive mid-range theories.

Dramatic operational and financial improvements were achieved for the case firm. Significant and unintended environmental and social benefits were also found. A design proposition (DP) and several mid-range theories are proposed as an extension of AR research to DSR research.

A problem-solving DSR research can be better assessed by the intervention-based DSR framework developed in this study. DSR studies should be encouraged for both practical and theoretical advancement purposes.

A challenging business problem-solving study can be tackled effectively through an industry/academic collaboration taking a PAR approach to deliver substantial values and organization transformational results.

Drivers and store associates are safer with smart delivery operations in the case firm.

There are still limited PAR design science case studies in the supply chain/logistics research literature. The research experience and findings gained from this study provide more insights toward how this type of research can be conducted and assessed.

In the Norwegian oil and gas industry the upstream logistics includes providing the offshore installations with needed supplies and return flow of used materials and equipment. This paper considers a real‐life routing problem for supply vessels serving offshore installations at Haltenbanken off the northwest coast of Norway from its onshore supply base. The purpose of the paper is to explore how the offshore installation's limited storage capacity affects the routing of the supply vessels aiming towards creating efficient routes.

A simplified version of the real‐life routing problem for one supply vessel is formulated as a mixed integer linear programming model that contains constraints reflecting the storage requirements problem. These constraints ensure that there is enough capacity at the platform decks and that it is possible to perform both pickup and delivery services.

The model has been tested on real‐life‐sized instances based on data provided by the Norwegian oil company Statoil ASA. The tests show that in order to obtain optimal solutions to the pickup and delivery problem with limited free storage capacities at installations, one has to include in the formulation the new sets of constraints, the storage feasibility and the service feasibility requirements. In addition, two visits to some platforms are necessary to obtain optimality.

The main limitation is the present inability to solve large cases.

The contribution of this paper is to provide a better insight into a real‐life routing problem which has a unique feature arising from the limited deck capacity at the offshore installations that complicates the performance of service. This feature has neither been discussed nor modeled in the vehicle routing literature before, hence the formulation of the problem is original and reveals some interesting results.